Classifications

• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
  • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
  • G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
  • G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
  • G06F16/7837—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using objects detected or recognised in the video content
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
  • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
  • G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
  • G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
  • H04N23/60—Control of cameras or camera modules
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
  • H04N23/60—Control of cameras or camera modules
  • H04N23/695—Control of camera direction for changing a field of view, e.g. pan, tilt or based on tracking of objects

Definitions

• the technology of the present disclosure relates to an image file, an information processing device, an imaging device, and a generation method.
• JP 2021-177317A discloses a three-dimensional model construction system.
• the three-dimensional model construction system described in JP-A-2021-177317 includes a management means, a collection means, a generation means, and a provision means.
• the management means manages each of the plurality of mobile objects in association with a user.
• the collecting means collects photographic data including supplementary information regarding the photographing, which is photographed by a photographing device provided in each of the plurality of moving objects.
• the generating means generates a three-dimensional model using the photographic data collected by the collecting means.
• the granting means grants a reward to a user associated with a mobile object that has photographed the photographic data, in accordance with photographic data used in generating the three-dimensional model by the generating means.
• the generation means uses additional information included in the new imaging data to specify the imaging area of the existing 3D model corresponding to the new imaging data, and generates a 3D model from the new imaging data in the imaging area.
• the existing three-dimensional model is updated using new imaging data according to the difference between the dimensional model and the existing three-dimensional model.
• One embodiment of the technology of the present disclosure provides an image file, an information processing device, an imaging device, and a generation method that allow the content of an image file to be grasped without reproducing the image file.
• the first aspect according to the technology of the present disclosure is an image file having the following configuration. That is, the image file according to the first aspect includes moving image data including a group of frames and supplementary information, the supplementary information includes first supplementary information and second supplementary information, and the first supplementary information includes: The information is information regarding all frames included in the frame group, and the second supplementary information is information regarding some frames in the frame group.
• a second aspect of the technology of the present disclosure is a generation method for generating an image file including moving image data including a group of frames and incidental information, the method comprising: an acquisition step of obtaining the moving image data; a first adding step of adding first incidental information, which is information about all frames included in the image file, to the image file as incidental information; and a first attaching step, which adds second incidental information, which is information about some frames of the frame group.
• This generation method includes a second adding step of adding information to the image file.
• FIG. 2 is a conceptual diagram showing an example of a mode in which an imaging device is used.
• FIG. 2 is a block diagram illustrating an example of the electrical hardware configuration and main functions of the imaging device.
• FIG. 3 is a conceptual diagram illustrating an example of processing contents for acquiring moving image data, processing contents for acquiring image recognition result information, and processing contents for acquiring frame-related information.
• FIG. 7 is a conceptual diagram illustrating an example of processing contents for acquiring a group of complaint-related information by period, processing contents for acquiring scene information, and processing contents for partly acquiring plural frame-related information.
• FIG. 7 is a conceptual diagram illustrating an example of processing contents for acquiring summary information and processing contents for acquiring overall related information.
• FIG. 2 is a conceptual diagram illustrating an example of processing contents for generating a moving image file including moving image data and metadata.
• FIG. 7 is a conceptual diagram showing an example of a mode in which frame-related information, partial frame-related information, and overall related information are stored (recorded) in a video file as meta information.
• FIG. 2 is a conceptual diagram illustrating an example of processing contents for adding file-related information to a moving image file.
• FIG. 3 is a conceptual diagram showing an example of the structure of image recognition result information.
• FIG. 2 is a conceptual diagram illustrating an example of a process for adding some frame-related information to a moving image file.
• FIG. 2 is a conceptual diagram illustrating an example of processing contents for adding overall related information to a moving image file.
• FIG. 2 is a conceptual diagram showing an example of a structure of metadata.
• FIG. 3 is a conceptual diagram showing an example of processing contents of a control unit. 3 is a flowchart illustrating an example of the flow of image file creation processing.
• FIG. 12 is a conceptual diagram showing an example of processing contents for including subject change information in frame-related information and processing details for partially including representative subject change information in a plurality of frame-related information in an imaging apparatus according to a first modification.
• FIG. 7 is a conceptual diagram showing an example of processing details for acquiring geometric information in an imaging device according to a second modification.
• FIG. 12 is a conceptual diagram showing an example of processing contents for including geometric change information in frame-related information and processing contents for partially including representative geometric change information in plural frame-related information in an imaging device according to a second modification.
• FIG. 12 is a conceptual diagram showing an example of processing contents for including view angle change information in frame related information and processing contents for partially including representative view angle change information in a plurality of frame related information in an imaging device according to a third modification.
• FIG. 12 is a conceptual diagram showing an example of processing contents for including tracking-related information in frame-related information and processing details for partially including representative tracking-related information in plural frame-related information, in an imaging device according to a fourth modification.
• FIG. 12 is a conceptual diagram showing an example of processing contents for including pan-tilt information in frame-related information and processing contents for partially including representative pan-tilt information in plural frame-related information in an imaging apparatus according to a fifth modification.
• FIG. 12 is a conceptual diagram showing an example of processing contents for including view angle change information in frame related information and processing contents for partially including representative view angle change information in a plurality of frame related information in an imaging device according to a third modification.
• FIG. 12 is a conceptual diagram showing an example of processing contents for including tracking-related information in frame-related information
• FIG. 12 is a conceptual diagram showing an example of processing contents for including inertial sensor signal difference information in frame related information and processing details for partially including representative inertial sensor signal difference information in a plurality of frame related information in an imaging device according to a sixth modification.
• FIG. 10 is a conceptual diagram showing an example of processing contents for including recording time related information in frame related information and processing details for partially including representative recording time related information in a plurality of frame related information in an imaging apparatus according to a seventh modification.
• FIG. 12 is a conceptual diagram illustrating an example of a process for including operation-related information in frame-related information and a process for partially including representative operation-related information in a plurality of frame-related information in an imaging apparatus according to an eighth modification.
• FIG. 10 is a conceptual diagram showing an example of processing contents for including recording time related information in frame related information and processing details for partially including representative recording time related information in a plurality of frame related information in an imaging apparatus according to a seventh modification.
• FIG. 12 is a conceptual diagram illustrating an example of a process
• FIG. 12 is a conceptual diagram showing an example of processing contents for acquiring subject sensor information in an imaging device according to a ninth modification.
• FIG. 12 is a conceptual diagram showing an example of processing contents for including subject sensor information in frame-related information and processing details for partially including representative subject sensor information in a plurality of frame-related information in an imaging apparatus according to a ninth modification.
• FIG. 12 is a conceptual diagram showing an example of processing contents for including separate moving image file information in overall related information in an imaging device according to a tenth modification.
• FIG. 2 is a conceptual diagram showing an example of a mode in which an external device is caused to execute image file creation processing.
• the imaging device 10 images an imaging target area 12 designated as a subject.
• the range of the imaging target area 12 is determined by the angle of view specified by the user of the imaging device 10 (hereinafter referred to as "user").
• the imaging target area 12 includes people 12A to 12D, a road 12E, and the like.
• the imaging device 10 is an example of an “imaging device” according to the technology of the present disclosure.
• the imaging device 10 is a consumer digital camera with interchangeable lenses.
• the imaging device 10 includes an imaging device main body 14 and an interchangeable lens 16.
• the interchangeable lens 16 is replaceably attached to the imaging device main body 14. Note that although a digital camera with interchangeable lenses is cited here as an example of the imaging device 10, this is merely an example, and a digital camera with a fixed lens may also be used.
• the technology of the present disclosure does not apply even if the imaging device 10 is an industrial digital camera. also holds true. Further, the technology of the present disclosure is applicable even when the imaging device 10 is an imaging device installed in various electronic devices such as a drive recorder, a smart device, a wearable terminal, a cell observation device, an ophthalmology observation device, or a surgical microscope. do. Further, the technology of the present disclosure provides that the imaging device 10 can be used with various modalities such as an endoscope device, an ultrasound diagnostic device, an X-ray imaging device, a CT (Computed Tomography) device, or an MRI (Magnetic Resonance Imaging) device.
• CT Computer Tomography
• MRI Magnetic Resonance Imaging
• the imaging device 10 is provided with a UI (User Interface) system device 18 .
• the UI device 18 is a device that accepts operations on the imaging device 10 and presents (for example, displays) various information to the user.
• the UI device 18 has a release button 20, a dial 22, a touch panel display 24, and an instruction key 26 that accepts various instructions.
• the release button 20 functions as an imaging preparation instruction section and an imaging instruction section, and provides imaging preparation instructions (for example, AF (Auto Focus) and AE (Auto Exposure) instructions) to the imaging device 10.
• imaging preparation instructions for example, AF (Auto Focus) and AE (Auto Exposure) instructions
• the dial 22 is operated when setting the operation mode and the like.
• various operation modes are selectively set by operating the dial 22.
• the operation mode includes the operation mode of the imaging system. Examples of the operation mode of the imaging system include a still image imaging mode, a moving image imaging mode, and the like.
• the touch panel display 24 includes a display 28 and a touch panel 30.
• An example of the display 28 is a liquid crystal display or an EL (Electroluminescent Display) display.
• the display 28 displays live view images, still images, moving images, menu screens, and the like. In the example shown in FIG. 1, a live view image is displayed on the display 28.
• the imaging device 10 generates moving image data 32 showing an image of the imaging target area 12 by imaging the imaging target area 12 at a frame rate for moving images.
• the moving image data 32 includes a frame group 34.
• the frame group 34 consists of a plurality of frames 36 (that is, a plurality of image data arranged in chronological order).
• the type of frame 36 is, for example, visible light image data obtained by imaging the imaging target region 12 in a visible light range.
• the type of frame 36 is not limited to this, and may be non-visible light image data obtained by imaging in a wavelength range other than the visible light range.
• the moving image data 32 is an example of "moving image data” according to the technology of the present disclosure.
• the frame group 34 is an example of a “frame group” according to the technology of the present disclosure.
• the frame 36 is an example of a "frame” according to the technology of the present disclosure.
• the imaging device 10 includes a UI device 18, an information processing device 38, an image sensor 40, and a communication I/F (Interface) 42.
• the information processing device 38 is an example of an “information processing device” according to the technology of the present disclosure.
• the information processing device 38 includes a processor 44, an NVM (Non-volatile memory) 46, and a RAM (Random Access Memory) 48.
• processor 44 is an example of a "processor" according to the technology of the present disclosure.
• the processor 44 is a processing device that includes a DSP (Digital Signal Processor), a CPU (Central Processing Unit), and a GPU (Graphics Processing Unit), and the DSP and GPU operate under the control of the CPU and execute image-related processing.
• a processing device including a DSP, a CPU, and a GPU is cited as an example of the processor 44, but this is just an example, and the processor 44 may be one or more CPUs and DSPs that integrate GPU functions. It may be one or more CPUs and DSPs that do not integrate GPU functions, or it may be equipped with a TPU (Tensor Processing Unit).
• the NVM 46 is a nonvolatile storage device that stores various programs, various parameters, and the like. Examples of the NVM 46 include flash memory (eg, EEPROM (Electrically Erasable and Programmable Read Only Memory)). RAM48 is
• RAM 48 a memory in which information is temporarily stored, and is used by the processor 44 as a work memory.
• Examples of the RAM 48 include DRAM (Dynamic Random Access Memory) and SRAM (Static Random Access Memory).
• the image sensor 40 is connected to the bus 50.
• An example of the image sensor 40 is a CMOS (Complementary Metal Oxide Semiconductor) image sensor.
• the image sensor 40 generates moving image data 32 by capturing an image of the imaging target area 12 (see FIG. 1) under the control of the processor 44.
• CMOS image sensor is cited as an example of the image sensor 40, but this is just an example, and the image sensor 40 may be another type of image sensor such as a CCD (Charge Coupled Device) image sensor. Good too.
• Image sensor 40 may be another type of image sensor such as a CCD (Charge Coupled Device) image sensor. Good too.
• the UI device 18 is connected to the bus 50.
• the UI device 18 accepts instructions from the user and outputs a signal indicating the accepted instructions to the processor 44. Further, the UI device 18 presents various information to the user under the control of the processor 44. Presentation of various information is realized by, for example, a display 28 (see FIG. 1), a speaker (not shown), and the like.
• the communication I/F 42 is an interface including a communication processor, an antenna, etc., and is connected to the bus 50.
• the communication standard applied to the communication I/F 42 is, for example, a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), or the like.
• the imaging device 10 generates a moving image file including the moving image data 32 by capturing an image in the moving image capturing mode.
• it is necessary to reproduce the moving image file In this case, for example, in order to understand the overall structure of the video data 32, it is necessary to reproduce most of the video data 32, and the frames 36 included in the video data 32 must be played back. The larger the number of images, the longer it takes to play.
• the processor 44 performs image file creation processing.
• the image file creation process is a process of creating an image file.
• the image file created by performing the image file creation process has additional information (for example, metadata) that will be described later.
• an image file creation program 52 is stored in the NVM 46.
• the processor 44 reads the image file creation program 52 from the NVM 46 and executes the read image file creation program 52 on the RAM 48 to perform image file creation processing.
• the image file creation process is realized by the processor 44 operating as an acquisition unit 44A, a generation unit 44B, a first application unit 44C, a second application unit 44D, and a control unit 44E according to an image file creation program 52 executed on the RAM 48. be done.
• the process performed by the acquisition unit 44A is an example of an "acquisition step” according to the technology of the present disclosure.
• the process performed by the first applying unit 44C is an example of a "first applying step” according to the technology of the present disclosure.
• the process performed by the second applying unit 44D is an example of a "second applying step” according to the technology of the present disclosure.
• the acquisition unit 44A acquires the moving image data 32 from the image sensor 40.
• the acquisition unit 44A acquires image recognition result information 54 recorded as metadata by performing an AI (Artificial Intelligence) image recognition process on each frame 36 included in the frame group 34 of the moving image data 32.
• the image recognition result information 54 is information indicating a result obtained by performing an AI-based image recognition process.
• the image recognition result information 54 includes information regarding the people 12A and 12B shown in the frame 36 and scene information 54A.
• the image recognition result information 54 is given an identifier (“#1” to “#N” in the example shown in FIG. 3) for each subject recognized by the image recognition process.
• the object recognized by the image recognition process is not limited to a single object, but also includes a combination of multiple objects.
• the information regarding the person 12A includes coordinates (i.e., two-dimensional coordinates) that can specify the position of the person 12A within the frame 36, and the type of the person 12A (in the example shown in FIG. 3, "human”). , “little girl", and “name (in the example shown in FIG. 3, the name is "Fuji Hanae")", and the attributes of the person 12A (in the example shown in FIG. 3, "running") are shown.
• information regarding the person 12B includes coordinates (i.e., two-dimensional coordinates) that allow the position of the person 12B within the frame 36 to be specified, the type of the person 12B (in the example shown in FIG. 3,
• the scene information 54A is information regarding the scene specified from the frame 36.
• the scene specified from the frame 36 is, for example, a combination of the person 12A and the person 12B.
• the scene information 54A shows information that "Hanae and Masae are playing."
• a combination of the person 12A and the person 12B is illustrated as a scene specified from the frame 36, but this is merely an example.
• the aspect of one subject for example, the person 12A, the person 12B, or a combination of the people 12A to 12D and scenery
• the obtained scene changes depending on the result obtained by performing AI-based image recognition processing.
• AI-based image recognition processing is illustrated here, the technology of the present disclosure is not limited to this, and template matching-based image recognition processing may be applied, or AI-based image recognition processing may be applied. and template matching-based image recognition processing may be used together.
• one or more labels may be added to the subject photographed in the frame 36 in response to an instruction given to the imaging device 10 from the outside (for example, an instruction accepted by the UI device 18). good. Further, one or more of the attached labels may be used as the image recognition result information 54. Examples of the label include coordinates by which the position of the subject within the frame 36 can be specified, the type of subject, and attributes of the subject.
• the acquisition unit 44A acquires frame-related information 56 for each frame 36 included in the frame group 34 of the video data 32.
• the frame related information 56 includes image recognition result information 54 corresponding to the frame 36 and frame basic information 58 corresponding to the frame 36.
• the frame related information 56 is an example of "information regarding one frame included in a frame group" according to the technology of the present disclosure.
• the frame basic information 58 includes a frame identifier, model information, lens information, date and time information, imaging condition information, and the like.
• the frame identifier is an identifier that can identify the frame 36.
• the model information is information indicating the model of the imaging device main body 14.
• the lens information is information indicating the type and specifications of the interchangeable lens 16 (see FIG. 1).
• the date and time information is the date and time when the frame 36 corresponding to the frame related information 56 was obtained (for example, the time expressed in year, month, day, hour, minute, and second).
• the imaging condition information is information indicating imaging conditions set for the imaging device 10 (for example, F number, shutter speed, sensitivity of the image sensor 40, 35mm equivalent focal length, and on/off of image stabilization). be.
• the acquisition unit 44A divides all the frame-related information 56 associated with the frame group 34 of the moving image data 32 into a plurality of frame-related information groups 60 and acquires them.
• the plurality of frame-related information groups 60 are obtained by dividing all the frame-related information 56 of a plurality of specified periods (in the example shown in FIG. 4, the first period to the Nth period).
• the frame related information group 60 is a set of a plurality of frame related information 56.
• the plurality of periods may be determined according to instructions received by the UI device 18. Further, the plurality of periods may be determined according to a preset algorithm. In this case, for example, all the frame related information 56 associated with the frame group 34 may be separated at time intervals that are uniquely determined according to the number of all frames 36 included in the frame group 34.
• the acquisition unit 44A acquires scene information 61 from the frame related information group 60 and the frame group 34 corresponding thereto.
• the scene information 61 is information regarding a scene specified from a plurality of frames 36 with which the frame related information group 60 is associated. Examples of the scenes identified from the plurality of frames 36 include lunch at a picnic, cooking at a picnic, fishing at a picnic, and the like.
• the scene information 61 includes, for example, text that can identify a scene, a mark that can identify a scene (for example, a pictogram), a thumbnail image that can identify a scene (for example, a thumbnail still image or a thumbnail video), and a combination of text and mark. It is expressed by a combination, a combination of text and a thumbnail image, a combination of a thumbnail image and a mark, a combination of text, a mark, and a thumbnail image, etc.
• the scene information 61 is obtained using a neural network (NN) 62, which is a type of mathematical model. Learning is performed on the NN 62 using a plurality of teacher data including information corresponding to a plurality of frame-related information groups 60 and correct data (here, as an example, information regarding a plurality of scenes).
• the NN 62 outputs scores regarding various scenes.
• the acquisition unit 44A inputs the frame related information group 60 to the NN 62.
• the acquisition unit 44A identifies a scene by referring to the score output from the NN 62 when the frame related information group 60 is input to the NN 62, and acquires information regarding the identified scene as scene information 61.
• a scene identified from a plurality of frames 36 to which the frame-related information group 60 is associated is identified using the NN 62, this is just an example.
• a scene determined for each period may be applied according to instructions given by the user to the imaging device 10 via the UI device 18 or a device indirectly or directly connected to the imaging device 10. Good too.
• the acquisition unit 44A acquires some of the frame-related information 64 in units of the frame-related information group 60.
• the partial multiple frame related information 64 includes scene information 61 specified from the corresponding frame related information group 60 and period-specific basic information 66.
• the partial multiple frame related information 64 is an example of "information regarding a partial plurality of frames of the frame group" according to the technology of the present disclosure.
• the period-specific basic information 66 includes a frame identifier, model information, lens information, time information, imaging condition information, and the like.
• the frame identifier included in the period-based basic information 66 is an identifier that can identify the frame 36 that contributed to obtaining the scene information 61 at a certain level or higher.
• An example of a frame 36 that has contributed to obtaining the scene information 61 at a certain level or above is a frame 36 associated with frame related information 56 whose score output from the NN 62 is a certain value or above.
• the model information included in the period-specific basic information 66 is model information that is statistically obtained from the plurality of frame-related information 56 included in the frame-related information group 60 (for example, the model information included most in the plurality of frame-related information 56).
• the lens information included in the period-specific basic information 66 is lens information that is statistically obtained from the plurality of frame-related information 56 included in the frame-related information group 60 (for example, the lens information included most in the plurality of frame-related information 56). lens information).
• the time information included in the period-based basic information 66 is information that includes two pieces of date and time information included in the first frame-related information 56 and the last frame-related information 56 of the frame-related information group 60. Further, the time information included in the period-based basic information 66 may be two frame identifiers included in the first frame-related information 56 and the last frame-related information of the frame-related information group 60. Further, the time information included in the period-specific basic information 66 is the date and time information included in the first frame related information 56 of the frame related information group 60 and the date and time information included in the last frame related information 56 of the frame related information group 60. The information may also be information indicating a time zone calculated from the information.
• the imaging condition information included in the period-based basic information 66 is the imaging condition information statistically obtained from the plurality of frame-related information 56 included in the frame-related information group 60 (for example, the imaging condition information included most in the plurality of frame-related information 56). (imaging condition information).
• the acquisition unit 44A acquires summary information indicating the outline of the moving image data 32.
• the summary is a title expressing the content shown in the video image data 32, a sentence expressing the content shown in the video image data 32, a mark expressing the content shown in the video image data 32, or a video image. It refers to a thumbnail image or the like that expresses the content shown in the data 32.
• time zone specific summary information 68 and overall summary information 70 are listed as examples of summary information.
• the time period summary information 68 is information indicating an overview of the video data 32 by time period.
• the summary by time period may be, for example, a summary of each video data obtained by equally dividing the video data 32, or a summary of the video data 32 divided into periods 1 to N as shown in FIG. This is an overview of each of the obtained moving image data.
• the overall overview information 70 is information indicating an overview of the entire moving image data 32.
• the time period summary information 68 and the overall summary information 70 are specified from, for example, a plurality of partial frame-related information 64. In the following, when it is not necessary to explain the time zone summary information 68 and the overall summary information 70 separately, they will be referred to as "summary information" without a reference numeral.
• the summary information is obtained using the NN72.
• learning is performed using a plurality of pieces of teacher data including information corresponding to a plurality of partial multi-frame related information 64 and correct answer data (here, as an example, information regarding a plurality of summaries).
• the NN 72 outputs scores regarding various summaries.
• the acquisition unit 44A inputs one or more partial plural frame related information 64 to the NN 72.
• the acquisition unit 44A identifies a summary by referring to the score output from the NN 72 when one or more partial multiple frame related information 64 is input to the NN 72, and acquires information regarding the identified summary as summary information.
• the summary information is an example of "information regarding the structure of moving image data" according to the technology of the present disclosure.
• the NN 72 is trained using a plurality of pieces of teacher data including information corresponding to a plurality of partial multi-frame related information 64 and correct answer data.
• the teacher data may also include information corresponding to a plurality of pieces of frame-related information 56.
• a determined outline may be applied according to instructions given by the user to the imaging device 10 via the UI device 18 or a device indirectly or directly connected to the imaging device 10.
• summary information is illustrated here, this is just an example.
• information indicating the types of all subjects shown in the video data 32 information showing geographical features identified from the scenery shown in the video data 32, etc.
• information indicating a common subject appearing in the moving image data 32 may be applied.
• the information applied instead of or together with the summary information may be any information as long as it is related to the structure of the moving image data 32.
• the acquisition unit 44A acquires the overall related information 74.
• the overall related information 74 includes time zone summary information 68, overall summary information 70, and overall basic information 76.
• the overall basic information 76 includes a frame identifier, model information, lens information, time information, and imaging condition information.
• the frame identifier included in the overall basic information 76 is an identifier that can identify the frame 36 that contributed to obtaining the summary information at a certain level or higher.
• An example of a frame 36 that has contributed to obtaining summary information at a certain level or above is a frame 36 that is associated with some of the frame related information 64 whose score output from the NN 72 is a certain value or above.
• the model information included in the overall basic information 76 is model information that is statistically obtained from the plurality of partial multi-frame related information 64 (for example, the model information that is most included in the plural partial multi-frame related information 64). It is.
• the lens information included in the overall basic information 76 is lens information that is statistically obtained from the plurality of partial frame-related information 64 (for example, the lens information that is most included in the plurality of partial frame-related information 64). It is.
• the time information included in the overall basic information 76 is the start time and end condition of the moving image data 32. Further, the time information included in the overall basic information 76 may be the time required to reproduce the moving image data 32.
• the imaging condition information included in the overall basic information 76 is the imaging condition information statistically obtained from the plurality of partial frame-related information 64 (for example, the image capturing condition information that is most frequently included in the plurality of partial frame-related information 64). condition information).
• the moving image identifier included in the overall basic information 76 is an identifier uniquely given to the entire moving image data 32. Note that the overall basic information 76 includes the bit rate of the moving image data 32, the codec used for encoding and decoding the moving image data 32, etc. as other basic information regarding the entire moving image data 32. It may be
• the generation unit 44B generates a moving image file 78.
• the moving image file 78 has metadata 80.
• the metadata 80 is data related to the moving image data 32 (that is, data attached to the moving image data 32).
• the moving image file is an example of an "image file” according to the technology of the present disclosure.
• the metadata 80 is an example of "supplementary information" according to the technology of the present disclosure.
• a plurality of frame-related information 56 is saved (recorded) as metadata 80 in a moving image file 78.
• a plurality of pieces of partial frame-related information 64 that is, information including scene information 61 and period-specific basic information 66
• the overall related information 74 that is, the information including the time zone summary information 68, the overall summary information 70, and the overall basic information 76
• the plurality of partial multi-frame related information 64 is also used as metadata 80 in the moving image. It is saved in file 78.
• the second adding unit 44D adds the frame-related information 56 to the video file 78 by including the frame-related information 56 acquired for each frame 36 by the acquisition unit 44A in the metadata 80.
• the image recognition result information 54 included in the frame related information 56 added to the moving image file 78 is classified into a plurality of categories.
• a subject identifier in the example shown in FIG. 9, "#1" is a unique identifier for each subject photographed in the frame 36 (for example, person 12A, person 12B, and each combination of person 12A and person 12B). and “#2”).
• a plurality of categories such as a type category, an attribute category, and a position category, are assigned to the subject identifier.
• a plurality of categories are provided in a hierarchical manner for each of the type category and attribute category.
• the lower hierarchy is provided with categories of lower concepts or derived concepts of the upper hierarchy.
• information regarding the person 12A is assigned to "#1"
• information regarding the person 12B is assigned to "#2".
• the type category is a category that indicates the type of subject. In the example shown in FIG. 9, "human" is assigned to the type category as the type of subject.
• a gender category and a name category are provided in a hierarchy lower than the type category.
• the gender category is a category that indicates gender
• the name category is a category that indicates the name of a subject (for example, a common noun or a proper noun).
• the attribute category is a category that indicates the attribute of the subject.
• an action category, an expression category, and a clothing category are provided, and a color category is provided as a hierarchy below the clothing category.
• the motion category is a category indicating the motion of the subject.
• the facial expression category is a category that indicates the facial expression of the subject.
• the clothing category is a category that indicates the type of clothing that the subject is wearing.
• the color category is a category that indicates the color of clothes worn by the subject.
• the position category is a category that indicates the position of the subject within the frame 36.
• coordinate information that allows the location of the person 12A to be specified is assigned to “#1”
• coordinate information that allows the location of the person 12B to be specified is assigned to “#2”. It is being
• the coordinate information is, for example, the two-dimensional coordinates of the upper left corner of the bounding box (that is, the rectangular frame surrounding the subject in the frame 36) obtained by AI-based image recognition processing, and the two-dimensional coordinates of the lower right corner of the bounding box. be.
• various information included in the frame basic information 58 may also be hierarchically classified by category in the same manner as the image recognition result information 54.
• the second adding unit 44D includes the plurality of partial multiple frame related information 64 acquired by the acquisition unit 44A in the metadata 80. is added to the moving image file 78.
• the plurality of frame related information 56 and the plurality of partial multiple frame related information 64 included in the metadata 80 are an example of "second supplementary information" according to the technology of the present disclosure.
• the first adding unit 44C adds the overall related information 74 to the video file 78 by including the overall related information 74 acquired by the acquiring unit 44A in the metadata 80.
• the overall related information 74 included in the metadata 80 is an example of "first supplementary information" and "information regarding all frames included in a frame group" according to the technology of the present disclosure.
• the metadata 80 has a hierarchical structure.
• the layered structure has an upper layer, a middle layer, and a lower layer.
• Information regarding the entire frame group 34 is stored in the upper layer.
• the middle layer information regarding a plurality of frames 36 obtained by dividing the frame group 34 into periods shown in FIG. 4 is stored.
• Information regarding the frame 36 is stored in the lower layer.
• the overall related information 74 is stored in the upper layer, a part of the multiple frame related information 64 is stored in the middle layer, and the frame related information 56 is stored in the lower layer.
• a plurality of pieces of partial multi-frame related information 64 exist in one layer below the overall related information 74, and a plurality of frame related information 56 exists in a layer one below the partial plural frame related information 64. are doing.
• the control unit 44E stores the moving image file 78 obtained as described above in the NVM 46.
• the example shown in FIG. 13 shows an example in which the moving image file 78 is stored in the NVM 46, this is just an example.
• the moving image file 78 may be stored in one or more storage media other than the NVM 46.
• the storage medium may be any medium that is directly or indirectly connected to the imaging device 10 using a wired method, a wireless method, or the like. Examples of the storage medium include a DVD (Digital Versatile Disc), a USB (Universal Serial Bus) memory, an SSD (Solid State Drive), an HDD (Hard Disk Drive), or a magnetic tape drive.
• DVD Digital Versatile Disc
• USB Universal Serial Bus
• SSD Solid State Drive
• HDD Hard Disk Drive
• the process flow shown by the flowchart shown in FIG. 14 is an example of a "generation method" according to the technology of the present disclosure.
• step ST10 the acquisition unit 44A acquires the moving image data 32 from the image sensor 40 (see FIG. 3). After the process of step ST10 is executed, the image file creation process moves to step ST12.
• step ST12 the acquisition unit 44A acquires image recognition result information 54 by performing AI-based image recognition processing on each frame 36 included in the frame group 34 of the moving image data 32 acquired in step ST10 (Fig. 3 reference). After the process of step ST12 is executed, the image file creation process moves to step ST14.
• step ST14 the acquisition unit 44A acquires frame-related information 56 for each frame 36 included in the frame group 34 of the moving image data 32 acquired in step ST10 (see FIG. 3).
• the frame related information 56 includes image recognition result information 54 and frame basic information 58 (see FIG. 3).
• step ST16 the acquisition unit 44A acquires a plurality of frame-related information groups 60 from all the frame-related information 56 associated with the frame group 34 of the moving image data 32 acquired in step ST10 (see FIG. 4). After the process of step ST16 is executed, the image file creation process moves to step ST18.
• step ST18 the acquisition unit 44A acquires the scene information 61 in units of the frame-related information group 60 acquired in step ST16 (see FIG. 4).
• the scene information 61 is obtained by inputting the frame related information group 60 to the NN 62 and using the score output from the NN 62 .
• the image file creation process moves to step ST20.
• step ST20 the acquisition unit 44A acquires some of the frame-related information 64 in units of the frame-related information group 60 acquired in step ST16 (see FIG. 4).
• the partial multiple frame related information 64 includes scene information 61 and period-based basic information 66 (see FIG. 4).
• the image file creation process moves to step ST22.
• step ST22 the acquisition unit 44A acquires summary information (see FIG. 5).
• the summary information is obtained by inputting some of the multiple frame related information 64 acquired in step ST20 to the NN 72 and using the score output from the NN 72.
• the image file creation process moves to step ST24.
• step ST24 the acquisition unit 44A acquires the overall related information 74 (see FIG. 5).
• the overall related information 74 includes summary information and overall basic information 76 (see FIG. 5).
• step ST26 the image file creation process moves to step ST26.
• step ST26 the generation unit 44B generates a moving image file 78 including the moving image data 32 and metadata 80 acquired in step ST10 (see FIG. 6). After the process of step ST26 is executed, the image file creation process moves to step ST28.
• step ST28 the second adding unit 44D adds the frame-related information 56 to the video file 78 by including the frame-related information 56 acquired in step ST14 in the metadata 80 (see FIG. 8).
• step ST30 the image file creation process moves to step ST30.
• step ST30 the second adding unit 44D adds the partial plural frame related information 64 to the video file 78 by including the partial plural frame related information 64 acquired in step ST20 in the metadata 80 (Fig. 10).
• step ST30 the image file creation process moves to step ST32.
• step ST32 the first adding unit 44C adds the overall related information 74 to the video file 78 by including the overall related information 74 acquired in step ST24 in the metadata 80 (see FIG. 11).
• step ST34 the image file creation process moves to step ST34.
• step ST34 the control unit 44E stores the moving image file 78 obtained by executing the processes in steps ST10 to ST32 in the NVM 46 (see FIG. 13). After the process of step ST34 is executed, the image file creation process ends.
• the moving image data 32 is acquired and the moving image file 78 including the moving image data 32 is generated.
• the overall related information 74 is acquired as information regarding all the frames 36 included in the frame group 34 of the moving image data 32, and is added to the moving image file 78. Therefore, a user or the like (for example, a user or various devices) can understand the contents of all frames 36 included in the frame group 34 by referring to the overall related information 74 without playing back the video data 32. be able to.
• some multiple-frame related information 64 is acquired as information regarding some of the frames 36 included in the frame group 34 of the moving image data 32, and is added to the moving image file 78. Therefore, even without reproducing the video data 32, the user can grasp the contents of some of the frames 36 included in the frame group 34 by referring to the some of the frames related information 64. In this way, according to the imaging device 10 according to the present embodiment, the user or the like can understand the contents of the moving image data 32 without reproducing the moving image data 32.
• frame-related information 56 is acquired as information regarding one frame 36 included in the frame group 34 of the moving image data 32, and is added to the moving image file 78. Therefore, the user or the like can understand the content of one frame 36 included in the frame group 34 by referring to the frame related information 56 without reproducing the moving image data 32. Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• frame related information 56 is added to the moving image file 78.
• the frame related information 56 includes image recognition result information 54.
• the image recognition result information 54 includes scene information 54A.
• the scene information 54A is information regarding the scene specified from the frame 36. Therefore, the user or the like can grasp the scene specified from the frame 36 by referring to the scene information 54A included in the image recognition result information 54 of the frame related information 56, without reproducing the video data 32. be able to. Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• some of the multiple frame related information 64 is added to the moving image file 78.
• Part of the multiple frame related information 64 includes scene information 61.
• the scene information 61 is information regarding a scene specified from some of the frames 36 included in the frame group 34 of the video data 32 (that is, the frames 36 to which the frame-related information group 60 is associated). . Therefore, even if the user etc. do not play back the moving image data 32, by referring to the scene information 61 included in the partial plural frame related information 64, the user can It is possible to understand the scene specified from the plurality of frames 36. Thereby, it is possible to determine whether a frame 36 is important or not in units of a plurality of frames 36.
• the frame related information 56 includes the image recognition result information 54 and the frame basic information 58, but the technology of the present disclosure is not limited to this.
• information regarding changes in the subject within the moving image data 32 may be included in the frame related information 56 and some of the multiple frame related information 64.
• the acquisition unit 44A acquires the subject change information 82 and includes it in the frame related information 56.
• the subject change information 82 is information regarding changes in the person 12A shown in the plurality of frames 36 of the moving image data 32.
• An example of information regarding a change in the person 12A is a motion vector of the person 12A captured in a plurality of temporally adjacent frames 36 (in the example shown in FIG. 15, two temporally adjacent frames 36), or Information based on motion vectors can be cited.
• the information based on the motion vector refers to, for example, information indicating the direction of movement of the person 12A, information indicating the amount of movement of the person 12A, or the like.
• information regarding changes in the person 12A include information regarding changes in the facial expression of the person 12A captured in a plurality of temporally sequential frames 36, and information regarding changes in optical elements (brightness or hue) of the person 12A. information, or information regarding a change in the size of the person 12A within the frame 36.
• the acquisition unit 44A acquires the representative subject change information 84 and includes a portion of the acquired representative subject change information 84 in the multiple frame related information 64.
• the representative subject change information 84 included in the partial multiple frame related information 64 is information obtained from one or more subject change information 82 included in one or more frame related information 56 corresponding to the partial multiple frame related information 64. be. For example, among the one or more pieces of subject change information 82, main subject change information 82 that satisfies a specified condition is set as representative subject change information 84.
• the subject change information 82 that satisfies the specified conditions is, for example, the subject change information 82 of the person 12A with the largest size, or the subject change information 82 with the greatest degree of change of the person 12A (for example, the subject change information 82 with the largest motion vector).
• Subject change information 82 is included.
• the representative subject change information 84 includes, for example, information such as "a person is walking to the left".
• the subject change information 82 and the representative subject change information 84 are examples of "change information" according to the technology of the present disclosure.
• the frame related information 56 includes the subject change information 82. Therefore, even without reproducing the video data 32, the user can check the change in the subject (here, the person 12A as an example) in units of frames 36 by referring to the subject change information 82 in the frame related information 56. can be grasped. Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• the representative subject change information 84 is partially included in the multiple frame related information 64. Therefore, even if the user does not play back the video data 32, by referring to the representative subject change information 84 in the partial frame related information 64, the user or the like can select a unit of some frames 36 included in the frame group 34. This allows you to understand changes in the subject. Thereby, it is possible to determine whether a frame 36 is important or not in units of a plurality of frames 36.
• Geometric information 86 is geometric information regarding the imaging device 10. Geometric information refers to, for example, the position of the imaging device 10, the attitude of the imaging device 10, the imaging direction of the imaging device 10, and the like. Examples of the geometric information 86 include position information 86A, posture information 86B, and imaging direction information 86C.
• the position information 86A is information regarding the position of the imaging device 10.
• Posture information 86B is information regarding the posture of the imaging device 10.
• the imaging direction information 86C is information in which the imaging direction (that is, the direction of the optical axis) of the imaging device 10 is expressed as an orientation.
• the imaging device 10 is provided with a GNSS (Global Navigation Satellite System) receiver 88, an inertial sensor 90, and a geomagnetic sensor 92.
• a GNSS receiver 88 , an inertial sensor 90 , and a geomagnetic sensor 92 are connected to processor 44 .
• GNSS receiver 88 receives radio waves transmitted from multiple satellites 94.
• the inertial sensor 90 measures physical quantities (eg, angular velocity and acceleration) indicating three-dimensional inertial motion of the imaging device 10, and outputs an inertial sensor signal indicating the measurement result.
• the geomagnetic sensor 92 detects geomagnetism and outputs a geomagnetic sensor signal indicating the detection result.
• the acquisition unit 44A calculates the latitude, longitude, and altitude that can specify the current position of the imaging device 10 as position information 86A. Furthermore, the acquisition unit 44A calculates posture information 86B (for example, information defined by a yaw angle, a roll angle, and a pitch angle) based on the inertial sensor signal input from the inertial sensor 90. Furthermore, the acquisition unit 44A calculates imaging azimuth information 86C based on the inertial sensor signal input from the inertial sensor 90 and the geomagnetic sensor signal input from the geomagnetic sensor 92. Furthermore, the acquisition unit 44A calculates the imaging posture of the imaging device 10 (whether the long side direction of the camera is oriented vertically or horizontally) from the information of the inertial sensor 90.
• posture information 86B for example, information defined by a yaw angle, a roll angle, and a pitch angle
• imaging azimuth information 86C based on the inertial sensor signal input from the inertial sensor 90 and the geom
• the acquisition unit 44A acquires the geometric change information 96 and includes it in the frame related information 56.
• the geometric change information 96 is information regarding changes in the geometric information 86 between a plurality of frames 36 (in the example shown in FIG. 17, two temporally adjacent frames 36).
• the geometrical change information 96 includes the absolute value of the difference in the position information 86A between the plurality of frames 36, the absolute value of the difference in the posture information 86B between the plurality of frames 36, and the absolute value of the difference in the imaging direction information 86C. Contains absolute values.
• the absolute value of the difference is illustrated here, a ratio may be applied instead of the absolute value of the difference, and any index may be used as long as the degree of difference can be specified.
• the absolute value of the difference is illustrated below, the same thing can be said.
• the acquisition unit 44A acquires the representative geometric change information 98 and includes a portion of the acquired representative geometric change information 98 in the multiple frame related information 64.
• the representative geometric change information 98 is information obtained from one or more geometric change information 96 included in one or more frame related information 56 that partially corresponds to the multiple frame related information 64. For example, among the one or more pieces of geometric change information 96, the geometric change information 96 that satisfies a specified condition is set as representative geometric change information 98.
• a first example of the geometrical change information 96 that satisfies the specified conditions is geometrical change information 96 that has the largest degree of change in the geometrical information 86, and geometrical change information 96 that has the smallest degree of change in the geometrical information 86.
• Examples include geometric change information 96 or geometric change information 96 having information corresponding to the median value of a plurality of pieces of geometric change information 96.
• a second example of the geometrical change information 96 that satisfies the specified condition is the geometrical change information 96 that has the largest absolute value of the difference in position information 86A between the plurality of frames 36.
• Examples include geometric change information 96 in which the absolute value of the difference between the position information 86A is the smallest, or geometric change information 96 in which the absolute value of the difference in the position information 86A between the plurality of frames 36 is the median value.
• a third example of the geometrical change information 96 that satisfies the specified condition is the geometrical change information 96 that has the largest absolute value of the difference in posture information 86B between the plurality of frames 36.
• Examples include geometric change information 96 in which the absolute value of the difference between the posture information 86B is the smallest, or geometric change information 96 in which the absolute value of the difference in the posture information 86B between the plurality of frames 36 is the median value.
• a fourth example of the geometrical change information 96 that satisfies the specified condition is the geometrical change information 96 with the largest absolute value of the difference in the imaging direction information 86C between the plurality of frames 36, and the geometrical change information 96 between the plurality of frames 36.
• the geometric change information 96 has the smallest absolute value of the difference in the imaging azimuth information 86C between the frames 36, or the geometric change information 96 has the median absolute value of the difference in the imaging azimuth information 86C between the plurality of frames 36. Can be mentioned.
• the geometric change information 96 and the representative geometric change information 98 are examples of "change information" according to the technology of the present disclosure.
• the frame related information 56 includes the geometric change information 96. Therefore, the user or the like can grasp the change in the position or orientation of the imaging device 10 in units of frames 36 by referring to the geometric change information 96 in the frame related information 56 without reproducing the video data 32. be able to. Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• the representative geometrical change information 98 is partially included in the multiple frame related information 64. Therefore, even if the user does not play back the video data 32, by referring to the representative geometrical change information 98 in the partial frame related information 64, the user or the like can reproduce some of the frames included in the frame group 34. Changes in the position or orientation of the imaging device 10 can be grasped in units of 36. Thereby, it is possible to determine whether a frame 36 is important or not in units of a plurality of frames 36.
• the frame-related information 56 includes geometric change information 96
• the frame-related information 64 partially includes representative geometric change information 98.
• the technology of the present disclosure is not limited thereto.
• information indicating a change in the angle of view of the imaging device 10 may be included in the frame related information 56 and some of the multiple frame related information 64.
• the acquisition unit 44A acquires the angle of view change information 100 and includes it in the frame related information 56.
• View angle information 102 is associated with the frame 36 .
• the view angle information 102 is information regarding the view angle set in the imaging device 10 (for example, the focal length associated with a change in zoom magnification).
• An example of the view angle change information 100 is the absolute value of the difference in the view angle information 102 between a plurality of frames 36 (in the example shown in FIG. 18, two temporally adjacent frames 36).
• the acquisition unit 44A acquires the representative angle of view change information 104 and includes a portion of the acquired representative angle of view change information 104 in the multiple frame related information 64.
• the representative view angle change information 104 is information obtained from one or more view angle change information 100 included in one or more frame related information 56 that partially corresponds to the multiple frame related information 64. For example, among the one or more pieces of view angle change information 100, the view angle change information 100 that satisfies a specified condition is set as the representative view angle change information 104.
• view angle change information 100 that satisfies the specified condition, for example, view angle change information 100 with the largest degree of change in the view angle information 102, view angle change information 100 with the smallest degree of change in the view angle information 102, Alternatively, the view angle change information 100 that corresponds to the median value among the plurality of view angle change information 100 may be mentioned.
• the view angle change information 100 and the representative view angle change information 104 are examples of "change information" according to the technology of the present disclosure. Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• the frame related information 56 includes the angle of view change information 100. Therefore, even without reproducing the video data 32, the user can grasp changes in the angle of view of the imaging device 10 in units of frames 36 by referring to the angle of view change information 100 in the frame related information 56. can.
• the representative view angle change information 104 is partially included in the multiple frame related information 64. Therefore, even if the user etc. do not play back the video data 32, by referring to the representative view angle change information 104 in the partial frame related information 64, the user can easily view some of the frames 36 included in the frame group 34. Changes in the angle of view of the imaging device 10 can be grasped in units of units. Thereby, it is possible to determine whether a frame 36 is important or not in units of a plurality of frames 36.
• the frame-related information 56 includes the angle-of-view change information 100, and some of the frame-related information 64 includes the representative angle-of-view change information 104.
• the technology of the present disclosure is not limited to this.
• information regarding subject tracking may be included in the frame related information 56 and some of the multiple frame related information 64.
• the acquisition unit 44A acquires the tracking related information 106 in units of frames 36, and includes the acquired tracking related information 106 in the corresponding frame related information 56.
• the tracking related information 106 is, for example, coordinates that specify the position of a tracking frame 106A (for example, an AF frame) that tracks the person 12A within the frame 36.
• the coordinates for specifying the position of the tracking frame 106A include, for example, the two-dimensional coordinates of the upper left corner of the tracking frame 106A and the two-dimensional coordinates of the upper right corner of the tracking frame 106A when the upper left corner of the frame 36 is the origin.
• the tracking related information 106 may include information indicating that the tracking mode is set, or the characteristics of the subject being tracked (for example, the type of subject or the subject's characteristics). (attributes, etc.) may also be included. In this way, the tracking related information 106 may be any information as long as it is information related to tracking the subject.
• the acquisition unit 44A acquires the representative tracking related information 108 and includes a portion of the acquired representative tracking related information 108 in the multiple frame related information 64.
• the representative tracking related information 108 is information obtained from one or more tracking related information 106 included in one or more frame related information 56 that partially corresponds to the multiple frame related information 64. For example, among the one or more pieces of tracking-related information 106, the tracking-related information 106 that satisfies a specified condition is set as the representative tracking-related information 108.
• the tracking related information 106 that satisfies the specified condition for example, the tracking related information 106 corresponding to the frame 36 having the tracking frame 106A that overlaps most with the tracking frames 106A of other frames 36 can be mentioned.
• the tracking related information 106 and the representative tracking related information 108 are examples of "information related to subject tracking" according to the technology of the present disclosure.
• the frame-related information 56 includes the tracking-related information 106. Therefore, even if the user does not play the moving image data 32, by referring to the tracking related information 106 in the frame related information 56, the user can grasp information related to tracking of the subject in units of frames 36. Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• the representative tracking related information 108 is partially included in the multiple frame related information 64. Therefore, even if the user etc. do not play the video data 32, by referring to the representative tracking related information 108 in the partial multiple frame related information 64, the user can select a unit of some of the multiple frames 36 included in the frame group 34. You can grasp information regarding tracking of the subject. Thereby, it is possible to determine whether a frame 36 is important or not in units of a plurality of frames 36.
• the acquisition unit 44A acquires the pan-tilt information 110 for each frame 36, and includes the acquired pan-tilt information 110 in the corresponding frame-related information 56.
• the pan/tilt information 110 is information regarding panning and information regarding tilt in a situation where the tracking mode is not set.
• the pan/tilt information 110 includes information indicating the amount of panning and information indicating the amount of tilt between a plurality of temporally adjacent frames 36 (for example, two temporally adjacent frames 36). .
• pan amount and tilt amount are calculated based on, for example, an inertial sensor signal output from the inertial sensor 90 (see FIG. 16).
• the pan-tilt information 110 information regarding panning and information regarding tilting in a situation where the tracking mode is not set is illustrated, but the technology of the present disclosure is not limited to this.
• the pan/tilt information 110 may be information regarding panning and information regarding tilting in a situation where the tracking mode is set.
• pan amount and tilt amount are illustrated here, the technology of the present disclosure is not limited to this, and instead of the pan amount and tilt amount, or in addition to the pan amount and tilt amount, the pan speed and tilt amount are Other physical quantities related to panning and tilting, such as speed, may also be applied.
• panning and tilting are just examples, and instead of the pan-tilt information 110 or together with the pan-tilt information 110, information regarding movement when the imaging device 10 moves in the horizontal direction (for example, the amount of movement and the speed of movement, etc.) ), and information regarding movement when the imaging device 10 moves in the vertical direction may be applied.
• the acquisition unit 44A acquires the representative pan-tilt information 112 and includes a portion of the acquired representative pan-tilt information 112 in the multiple-frame related information 64.
• the representative pan/tilt information 112 is information obtained from one or more pan/tilt information 110 included in one or more frame related information 56 that partially corresponds to the multiple frame related information 64. For example, among one or more pieces of pan-tilt information 110, pan-tilt information 110 that satisfies a specified condition is set as representative pan-tilt information 112.
• a first example of pan/tilt information 110 that satisfies the specified condition is pan/tilt information 110 with a maximum or minimum pan amount.
• pan-tilt information 110 that satisfies the specified condition is pan-tilt information 110 with a maximum or minimum tilt amount.
• pan/tilt information 110 that satisfies the specified condition is pan/tilt information 110 in which both the pan amount and the tilt amount are maximum or minimum.
• pan-tilt information 110 and the representative pan-tilt information 112 are an example of "information regarding movement of the imaging device" according to the technology of the present disclosure.
• the pan-tilt information 110 is included in the frame-related information 56. Therefore, even if the user does not play back the video data 32, by referring to the pan/tilt information 110 in the frame related information 56, the user can refer to the pan-related information (for example, pan amount) and the tilt-related information (for example, , tilt amount). Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• the pan-related information for example, pan amount
• the tilt-related information for example, tilt amount
• representative pan/tilt information 112 is included in part of the multiple frame related information 64. Therefore, even if the user does not play back the moving image data 32, by referring to the representative pan/tilt information 112 in the partial multiple frame related information 64, the user or the like can read the partial frames 36 included in the frame group 34.
• Information regarding panning for example, amount of panning
• information regarding tilting for example, amount of tilting
• the acquisition unit 44A acquires the inertial sensor signal difference information 114 in units of frames 36, and includes the acquired inertial sensor signal difference information 114 in the corresponding frame related information 56. .
• the inertial sensor signal difference information 114 is the absolute value of the difference between the inertial sensor signals 116 obtained before and after the time.
• the inertial sensor signal 116 is obtained from the inertial sensor 90 (see FIG. 16) for each frame 36.
• An example of the inertial sensor signal difference information 114 is the absolute value of the difference between two inertial sensor signals 116 corresponding to two temporally adjacent frames 36.
• the acquisition unit 44A acquires the representative inertial sensor signal difference information 118 and includes a portion of the acquired representative inertial sensor signal difference information 118 in the multiple frame related information 64.
• the representative inertial sensor signal difference information 118 is information obtained from one or more inertial sensor signal difference information 114 included in one or more frame related information 56 that partially corresponds to the multiple frame related information 64. For example, among the one or more pieces of inertial sensor signal difference information 114, inertial sensor signal difference information 114 that satisfies a specified condition is set as representative inertial sensor signal difference information 118.
• An example of the inertial sensor signal difference information 114 that satisfies the specified condition is the inertial sensor signal difference information 114 in which the absolute value of the difference between the two inertial sensor signals 116 is maximum or minimum.
• the inertial sensor signal difference information 114 and the representative inertial sensor signal difference information 118 are an example of "information regarding the first sensor” according to the technology of the present disclosure. Furthermore, in the sixth modification, the inertial sensor 90 (see FIG. 16) is an example of the "first sensor” according to the technology of the present disclosure.
• the frame related information 56 includes the inertial sensor signal difference information 114. Therefore, even without reproducing the moving image data 32, the user can refer to the inertial sensor signal difference information 114 in the frame related information 56 to determine the aspect of the imaging device 10 (for example, the image sensing device 10) in units of frames 36. posture, movement speed, etc.). Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• representative inertial sensor signal difference information 118 is included in part of the multiple frame related information 64. Therefore, even if the user does not play back the video data 32, by referring to the representative inertial sensor signal difference information 118 in the partial multiple frame related information 64, the user or the like can reproduce some of the multiple frames included in the frame group 34.
• the aspect of the imaging device 10 (for example, the attitude or moving speed of the imaging device 10) can be grasped in 36 units. Thereby, it is possible to determine whether a frame 36 is important or not in units of a plurality of frames 36.
• the acquisition unit 44A acquires the geomagnetic sensor signal difference information and the representative inertial sensor signal difference information from the geomagnetic sensor signal output from the geomagnetic sensor 92 (see FIG. 16) in the same manner as the inertial sensor signal difference information 114 and the representative inertial sensor signal difference information 118.
• Geomagnetic sensor signal difference information may also be acquired. In this case, the geomagnetic sensor signal difference information may be included in the frame related information 56 and the representative geomagnetic sensor signal difference information may be partially included in the multiple frame related information 64.
• the absolute value of the difference between the inertial sensor signals 116 is illustrated, but this is just an example, and for example, the ratio of one of the two inertial sensor signals 116 to the other. Any information that can identify the degree of difference between the inertial sensor signals 116 is sufficient.
• the inertial sensor 90 is cited as an example of the "first sensor" according to the technology of the present disclosure, but this is merely an example.
• the imaging device 10 is equipped with various sensors such as a distance sensor or a temperature sensor, and the signals output from the various sensors are handled in the same manner as the inertial sensor signal difference information 114, the present disclosure also applies.
• the technology will be established.
• the imaging device 10 is equipped with a distance measurement sensor, information based on the distance measurement results by the distance measurement sensor (for example, information indicating distances at several locations, or an image obtained by reducing a distance image) is It may be handled in the same manner as the inertial sensor signal difference information 114.
• the imaging device 10 is equipped with a temperature sensor
• information based on the measurement result by the temperature sensor for example, the outside temperature or an image obtained by reducing a thermal image
• the inertial sensor signal difference information 114 May be treated in the same manner.
• the frame-related information 56 includes the inertial sensor signal difference information 114, and the frame-related information 64 partially includes the representative inertial sensor signal difference information 118.
• the technology of the present disclosure is not limited thereto.
• information corresponding to the recording time during which the subject in the moving image data 32 is recorded may be included in the frame related information 56 and some of the plural frame related information 64.
• the acquisition unit 44A identifies a plurality of frames 36 in which the person 12A is continuously captured in the video data 32.
• the acquisition unit 44A acquires two imaging times 120.
• the imaging time 120 is the time when one frame worth of imaging was performed.
• One of the two imaging times 120 is the imaging time 120 corresponding to the first frame 36 of the plurality of frames 36 specified by the acquisition unit 44A, and the other is the imaging time 120 corresponding to the first frame 36 of the plurality of frames 36 specified by the acquisition unit 44A. This is an imaging time 120 corresponding to the last frame 36 of the frames 36.
• the acquisition unit 44A calculates recording time related information 122 based on the two imaging times 120.
• the recording time related information 122 refers to, for example, information indicating the elapsed time between two imaging times 120 (that is, the time during which the person 12A is continuously photographed in the moving image data 32). Note that here, the elapsed time between the two imaging times 120 is cited as the recording time related information 122, but this is just an example, and the recording time related information 122 is not limited to the two imaging times 120 themselves. Alternatively, it may be a frame identifier that can identify the two frames 36 corresponding to the two imaging times 120.
• the acquisition unit 44A includes the recording time related information 122 in the plurality of frame related information 56 corresponding to the plurality of frames 36 in which the person 12A is continuously photographed in the moving image data 32.
• the recording time related information 122 is specified one or more frame related information among the plurality of frame related information 56 corresponding to the plurality of frames 36 in which the person 12A is continuously photographed in the video data 32. 56.
• the recording time related information 122 may be included in the frame related information 56 corresponding to the first frame 36 or the last frame 36 of a plurality of frames 36 in which the person 12A is continuously shown in the video data 32. Just do it.
• the acquisition unit 44A acquires the representative recording time related information 124 and includes a portion of the acquired representative recording time related information 124 in the multiple frame related information 64.
• the representative recording time related information 124 is information obtained from one or more recording time related information 122 included in one or more frame related information 56 that partially corresponds to the multiple frame related information 64.
• the recording time related information 122 that satisfies a specified condition is set as the representative recording time related information 124.
• An example of the recording time-related information 122 that satisfies the specified conditions is whether the elapsed time between two imaging times 120 (that is, the time during which the person 12A is continuously photographed in the video image data 32) is the longest or the shortest. Recording time related information 122 is included.
• the recording time related information 122 and the representative recording time related information 124 are an example of "information corresponding to the recording time at which the subject in the video data is recorded" according to the technology of the present disclosure. It is.
• the frame related information 56 includes the recording time related information 122. Therefore, even if the user etc. do not play back the video data 32, by referring to the recording time related information 122 in the frame related information 56, a specific subject (for example, the person 12A) can be captured in the video in units of frames 36. It is possible to grasp the time continuously captured in the data 32. Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• representative recording time related information 124 is included in part of the multiple frame related information 64. Therefore, even if the user etc. do not play back the moving image data 32, by referring to the representative recording time related information 124 in the partial multiple frame related information 64, the user can easily view some of the multiple frames 32 included in the frame group 34. In units of units, it is possible to grasp the time period during which a specific subject (for example, the person 12A) is continuously shown in the moving image data 32. Thereby, it is possible to determine whether a frame 36 is important or not in units of a plurality of frames 36.
• the seventh modification described above shows an example in which the recording time related information 122 is included in the frame related information 56 and an example in which the representative recording time related information 124 is included in some of the plurality of frame related information 64.
• the technology of the present disclosure is not limited to this.
• information regarding operations on the imaging device 10 may be included in the frame related information 56 and some of the multiple frame related information 64.
• the acquisition unit 44A acquires the operation-related information 126 in units of frames 36, and includes the acquired operation-related information 126 in the corresponding frame-related information 56.
• the operation related information 126 is information indicating an operation performed on the imaging device 10 (for example, an operation accepted by the UI device 18).
• the acquisition unit 44A acquires the representative operation related information 127 and includes a portion of the acquired representative operation related information 127 in the multiple frame related information 64.
• the representative operation related information 127 is information obtained from one or more operation related information 126 included in one or more frame related information 56 that partially corresponds to the multiple frame related information 64. For example, among the one or more pieces of operation-related information 126, the operation-related information 126 that satisfies a specified condition is set as the representative operation-related information 127.
• An example of the operation-related information 126 that satisfies the specified condition is the most frequent operation or the least frequent operation among the plurality of operation-related information 126 included in all the frame-related information 56 that partially corresponds to the plurality of frame-related information 64. For example, operation related information 126 indicating .
• the operation-related information 126 and the representative operation-related information 127 are an example of "information related to an operation on an imaging device used in imaging to obtain moving image data" according to the technology of the present disclosure. be.
• the frame-related information 56 includes the operation-related information 126. Therefore, even if the user does not play the video data 32, by referring to the operation related information 126 in the frame related information 56, the user can grasp the operation performed on the imaging device 10 in units of frames 36. be able to. For example, in the frame 36 obtained while a menu setting operation is being performed on the imaging device 10, there is a low possibility that the user is focusing on the subject, and there is a high possibility that the frame is not an important frame for the user etc. . A user or the like can identify whether or not the frame 36 was obtained while a menu setting operation was performed on the imaging device 10 by referring to the operation-related information 126. Thereby, it is possible to determine in units of frames 36 whether or not the frames 36 are important.
• representative operation related information 127 is included in part of the multiple frame related information 64. Therefore, even if the user etc. do not play back the video data 32, by referring to the representative operation related information 127 in the partial multiple frame related information 64, the user or the like can perform a partial multiple frame 36 unit included in the frame group 34. With this, it is possible to understand the operations performed on the imaging device 10. Thereby, it is possible to determine whether a frame 36 is important or not in units of a plurality of frames 36.
• the frame-related information 56 and some of the multiple-frame related information 64 may include information regarding a sensor that measures the object in the video data 32 (for example, a physical quantity indicating the current state of the object, or a feature of the object, etc.). It's okay.
• the acquisition unit 44A acquires the subject sensor information 128 in units of frames 36.
• the subject sensor information 128 is information obtained from a sensor attached to the person 12A, who is the subject.
• a wearable terminal 130 is shown as a sensor attached to the person 12A.
• Wearable terminal 130 is a wristband type wearable terminal, and is worn on the wrist of person 12A.
• Wearable terminal 130 has a communication function and communicates with imaging device 10 .
• the wearable terminal 130 is equipped with a function to measure pulse. Wearable terminal 130 measures the pulse of person 12A, and transmits information indicating the measured pulse to imaging device 10 as subject sensor information 128. In the imaging device 10, the subject sensor information 128 transmitted from the wearable terminal 130 is received by the communication I/F 42, and the received subject sensor information 128 is acquired by the acquisition unit 44A.
• the acquisition unit 44A uses the subject sensor information 128 acquired from the wearable terminal 130 as the frame-related information of the corresponding frame 36 (that is, the frame 36 in which the person 12A shown in FIG. 24 is photographed). Included in 56.
• the acquisition unit 44A acquires the representative subject sensor information 132 and includes a portion of the acquired representative subject sensor information 132 in the multiple frame related information 64.
• the representative subject sensor information 132 is information obtained from one or more subject sensor information 128 included in one or more frame related information 56 that partially corresponds to the multiple frame related information 64.
• subject sensor information 128 that satisfies a specified condition is set as representative subject sensor information 132.
• An example of the representative subject sensor information 132 that satisfies the specified condition is a subject that exhibits the highest pulse rate among the plurality of subject sensor information 128 included in all the frame related information 56 that partially corresponds to the plurality of frame related information 64.
• Sensor information 128 is included.
• the subject sensor information 128 and the representative subject sensor information 132 are an example of "information regarding the second sensor that measures the subject in the moving image data" according to the technology of the present disclosure.
• the frame related information 56 includes the subject sensor information 128. Therefore, even if the user does not play back the video data 32, by referring to the subject sensor information 128 in the frame-related information 56, the user can determine the physical state of a specific subject (for example, the person 12A) in units of frames 36.
• the state for example, pulse rate, blood pressure, or blood sugar level
• the pulse of the person 12A is high, there is a high possibility that the person 12A is excited. That is, the frame 36 obtained by capturing the image of the excited person 12A is highly likely to be an important frame 36.
• the blood pressure of the person 12A is low, there is a high possibility that the person 12A is in poor physical condition.
• the ninth modification is applied to a scene where the person 12A is undergoing surgery at a hospital, it is possible to understand the medical procedure that had a large impact on the subject's physical condition. Therefore, by referring to the subject sensor information 128, the user or the like can determine whether or not each frame 36 is important.
• representative subject sensor information 132 is included in part of the multiple frame related information 64. Therefore, even if the user does not play back the video data 32, by referring to the representative subject sensor information 132 in the partial frame related information 64, the user or the like can select a unit of some of the frames 36 included in the frame group 34. With this, it is possible to grasp the physical condition (eg, pulse, blood pressure, or blood sugar level) of a specific subject (eg, person 12A). Thereby, it is possible to determine whether a frame 36 is important or not in units of a plurality of frames 36.
• the physical condition eg, pulse, blood pressure, or blood sugar level
• the wearable terminal 130 is illustrated in the present ninth modification, this is just an example, and it may be a smartphone or a tablet terminal, and one or more sensors such as a thermometer or a blood pressure monitor (i.e., Any electronic device may be used as long as it is equipped with a sensor capable of measuring objects in the moving image data 32.
• sensors such as a thermometer or a blood pressure monitor (i.e., Any electronic device may be used as long as it is equipped with a sensor capable of measuring objects in the moving image data 32.
• the ninth modification example has been described using an example in which the pulse of the person 12A is measured by the wearable terminal 130, this is merely an example.
• the measured information may be biological information such as blood pressure, breathing volume, number of breathing, or blood sugar level of the subject shown in the video image data 32.
• the information is not limited to biological information, but may be information measured by a sensor installed on the production line when the imaging target area is a production line of a factory or the like.
• the summary information and the overall basic information 76 are illustrated as information included in the overall related information 74, but the technology of the present disclosure is not limited to this.
• the moving image data 32 may be information related to a part of other moving image data
• the entire related information 74 may include information regarding the other moving image data.
• the first adding unit 44C Separate moving image file information 136 is included in the overall related information 74.
• the separate moving image file information 136 is information that specifies the location of the moving image file 134.
• the separate moving image file information 136 is, for example, an address in the memory. Furthermore, if the moving image file 134 exists on the Internet, the separate moving image file information 136 is, for example, a URL (Uniform Resource Locator).
• the separate moving image file information 136 is included in the metadata 134B of the moving image file 134, and the first adding unit 44C, when a part of the moving image data 134A is incorporated into the moving image data 32, Separate moving image file information 136 is acquired from the metadata 134B. Then, the first adding unit 44C adds the separate moving image file information 136 to the moving image file 78 by including the separate moving image file information 136 acquired from the metadata 134B in the overall related information 74.
• the separate moving image file information 136 is included in the overall related information 74.
• the separate moving image file information 136 is information that specifies the location of the source of a portion of the moving image data 134A. Therefore, even if the user does not play back the moving image data 32, by referring to the separate moving image file information 136 in the overall related information 74, the user can determine from which moving image file a part of the moving image data 32 is derived. It is possible to identify whether
• the tenth modification example has been described using an example in which a part of the video data 134A included in the video file 134 is incorporated into the video data 32, the technology of the present disclosure is limited to this. Not done. For example, if part of the video data included in one or more video files other than the video file 134 is incorporated into the video data 32 together with a part of the video data 134A, this tenth modification example also applies. In a similar manner, the separate moving image file information 136 may be included in the overall related information 74.
• the separate video file information 136 may include a thumbnail image (for example, a thumbnail still image or a thumbnail video) regarding a part of the video data 134A, or a frame included in a part of the video data 134A.
• the information may include an identifier for identifying the frame, the number of frames, or the like. In this way, the separate moving image file information 136 only needs to include information regarding part of the moving image data 134A.
• an image file is created by a computer 140 in an external device 138 that is communicably connected to the imaging device 10 via a network 137 such as a LAN (Local Area Network) or a WAN (Wide Area Network).
• the process may be executed.
• An example of the computer 140 is a server computer for cloud services.
• Computer 140 is an example of an "information processing device" according to the technology of the present disclosure.
• the computer 140 includes a processor 142, a storage 144, and a memory 146.
• the storage 144 stores an image file creation program 52.
• the imaging device 10 requests the external device 138 to execute image file creation processing via the network 137.
• the processor 142 of the external device 138 reads the image file creation program 52 from the storage 144 and executes the image file creation program 52 on the memory 146.
• the processor 142 performs image file creation processing according to the image file creation program 52 executed on the memory 146.
• the processor 142 then provides the processing results obtained by executing the image file creation processing to the imaging device 10 via the network 137.
• FIG. 27 shows an example of a configuration in which the external device 138 is caused to execute image file creation processing
• the imaging device 10 and the external device 138 may perform image file creation processing in a distributed manner, or a plurality of devices including the imaging device 10 and the external device 138 may perform image file creation processing in a distributed manner. It may also be executed.
• the frame related information 56, some of the frame related information 64, and the entire related information 74 are recorded in the metadata 80 of the video file 78.
• the technology of the present disclosure is not limited to this.
• a frame 36 is extracted from the moving image data 32 of the moving image file 78, an image file is generated for the extracted frame 36, and the generated image file includes the frame related information 56, some plural frame related information 64, and the overall related information. 74 may be added.
• the image file used is an image file in a format that allows additional information to be added to an area different from the image data (that is, a recordable format).
• the format of the video file may be any file format as long as it allows additional information to be added to an area different from the image data.
• the file format is MPEG (Moving Picture Experts Group)-4, H. 264, MJPEG (Motion JPEG), HEIF (High Efficiency Image File Format), AVI (Audio Video Interleave), MOV (QuickTime file format), WMV (Windows Media Video), FLV (Flash Video).
• HEIF video data is preferable.
• the items and number of additional information that can be added to an image file vary depending on the file format, and by updating the version information of the image file, additional information can be added for new items.
• the item of additional information means the viewpoint when adding additional information (that is, the category into which the information is classified).
• the image file creation program 52 may be stored in a portable computer-readable non-transitory storage medium such as an SSD, a USB memory, or a magnetic tape.
• An image file creation program 52 stored in a non-temporary storage medium is installed in the imaging device 10.
• the processor 44 executes image file creation processing according to the image file creation program 52.
• the image file creation program 52 is stored in a storage device such as another computer or a server device connected to the imaging device 10 via a network, and the image file creation program 52 is downloaded in response to a request from the imaging device 10. It may also be installed in the imaging device 10.
• the information processing device 38 is built into the imaging device 10 shown in FIG. 2, the technology of the present disclosure is not limited thereto. It's okay.
• the technology of the present disclosure is described using an example of a form realized by a software configuration, but the technology of the present disclosure is not limited to this, and can be implemented using an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Circuit), or an FPGA.
• a device including a Gate Array) or a PLD (Programmable Logic Device) may be applied. Also, hardware configuration
• a combination of and software configurations may also be used.
• processors can be used as hardware resources for executing the image file creation process described in the above embodiments.
• the processor include a CPU, which is a general-purpose processor that functions as a hardware resource for performing image file creation processing by executing software, that is, a program.
• the processor include a dedicated electronic circuit such as an FPGA, a PLD, or an ASIC, which is a processor having a circuit configuration specifically designed to execute a specific process.
• Each processor has a built-in or connected memory, and each processor uses the memory to execute image file creation processing.
• the hardware resources that execute the image file creation process may be configured with one of these various processors, or a combination of two or more processors of the same type or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Furthermore, the hardware resource that executes the image file creation process may be one processor.
• one processor is configured by a combination of one or more CPUs and software, and this processor functions as a hardware resource for executing image file creation processing.
• this processor functions as a hardware resource for executing image file creation processing.
• SoC System-on-a-chip
• a single IC (Integrated Circuit) chip can perform the functions of an entire system including multiple hardware resources that execute image file creation processing.
• SoC System-on-a-chip
• a processor that realizes this. In this way, the image file creation process is realized using one or more of the various processors described above as hardware resources.
• the grammatical concept "A or B” includes a concept synonymous with “at least one of A and B” in addition to the concept "one of A and B". included. That is, “A or B” includes the meaning that it may be only A, only B, or a combination of A and B. Further, in this specification, the same concept as “A or B” is applied when three or more items are expressed by connecting them with “or”.

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• 2023
  • 2023-02-15 CN CN202380030567.0A patent/CN118974719A/zh active Pending
  • 2023-02-15 WO PCT/JP2023/005309 patent/WO2023188940A1/ja not_active Ceased
  • 2023-02-15 JP JP2024511397A patent/JPWO2023188940A1/ja active Pending
• 2024
  • 2024-09-26 US US18/897,028 patent/US20250024154A1/en active Pending

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