CN111866366A - Method and apparatus for transmitting information - Google Patents
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- CN111866366A CN111866366A CN201910361344.8A CN201910361344A CN111866366A CN 111866366 A CN111866366 A CN 111866366A CN 201910361344 A CN201910361344 A CN 201910361344A CN 111866366 A CN111866366 A CN 111866366A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
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- 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
- H04N23/61—Control of cameras or camera modules based on recognised objects
Abstract
The embodiment of the disclosure discloses a method and a device for sending information. One embodiment of the method comprises: collecting a video of a shooting area; transmitting the collected video to a pre-integrated vision processor, so that the vision processor can execute the following operation steps: determining whether a predetermined event occurs in a photographing area based on the acquired video; determining a target video frame from the acquired video in response to determining that a predetermined event occurs in the photographing region; and storing the target video frame, and sending the target video frame. According to the embodiment, when the preset event occurs in the shooting area, the target video frame is stored and sent, and the flexibility of video processing is improved.
Description
Technical Field
The disclosed embodiments relate to the field of computer technologies, and in particular, to a method and an apparatus for transmitting information.
Background
The hot tide of artificial intelligence is currently rolling up various industries, and how to make various devices intelligent has become a research hotspot. The most popular deep learning in machine learning generally requires a large amount of computation. At present, data generated by the equipment can be processed in a cloud computing mode. The data generated by the device can also be processed by means of edge calculation. Edge computing can shorten data transmission distances by migrating computing from the cloud to an "edge" location closer to the data source being processed, as compared to cloud computing, thereby improving performance and reliability of the service. For example, some intelligent cameras have extremely strong end-up rational calculation power through an integrated vision processor, and have good performance in image processing.
Disclosure of Invention
The embodiment of the disclosure provides a method and a device for sending information.
In a first aspect, an embodiment of the present disclosure provides a method for sending information, where the method includes: collecting a video of a shooting area; transmitting the collected video to a pre-integrated visual processor, so that the visual processor executes the following operation steps: determining whether a predetermined event occurs in the shooting area based on the acquired video; determining a target video frame from the acquired video in response to determining that a predetermined event occurs in the shooting area; and storing the target video frame and sending the target video frame.
In some embodiments, the transmitting the target video frame includes: and sending the target video frame to a cloud end for processing by the cloud end.
In some embodiments, the transmitting the target video frame includes: and sending the target video frame through a preset USB interface so as to be displayed by a display device communicated with the USB interface.
In some embodiments, the predetermined event is the detection of a face image, and the vision processor runs a deep learning model for face detection; and the determining whether the predetermined event occurs in the photographing region based on the acquired video includes: for a video frame in the acquired video, carrying out face detection on the video frame by using the deep learning model; and in response to determining that the face image is detected in the video frame, determining that the predetermined event occurs in the shooting area.
In some embodiments, the determining a target video frame from the acquired video in response to determining that the predetermined event occurred in the shooting area includes: in response to determining that a face image is detected in the video frame, a predetermined number of video frames including the video frame are taken as target video frames.
In some embodiments, the predetermined event is detection of disappearance of the target item; and the determining whether the predetermined event occurs in the photographing region based on the acquired video includes: and matching the video frame with the previous video frame in the acquired video, and determining whether the target object in the shooting area disappears or not based on the matching result.
In some embodiments, the determining whether the target item in the shooting area disappears based on the matching result includes: and determining whether the target object in the shooting area disappears or not according to the data and the matching result acquired by the weight sensor, wherein the weight sensor is arranged in the shooting area and is used for acquiring the weight information of the object in the shooting area.
In some embodiments, the determining a target video frame from the captured video in response to determining that the predetermined event occurred in the capture area comprises: and in response to determining that the target object in the shooting area disappears, taking a predetermined number of video frames including the video frame as target video frames.
In a second aspect, an embodiment of the present disclosure provides an apparatus for transmitting information, the apparatus including: a capture unit configured to capture a video of a shooting area; an execution unit configured to transmit the acquired video to a pre-integrated vision processor for the vision processor to execute preset operation steps, wherein the vision processor comprises: a first determination unit configured to determine whether a predetermined event has occurred in the shooting area based on the acquired video; a second determination unit configured to determine a target video frame from the acquired video in response to a determination that a predetermined event has occurred in the shooting area; a transmitting unit configured to store the target video frame and transmit the target video frame.
In some embodiments, the transmitting unit is further configured to: and sending the target video frame to a cloud end for processing by the cloud end.
In some embodiments, the transmitting unit is further configured to: and sending the target video frame through a preset USB interface so as to be displayed by a display device communicated with the USB interface.
In some embodiments, the predetermined event is the detection of a face image, and the vision processor runs a deep learning model for face detection; and the first determination unit, further configured to: for a video frame in the acquired video, carrying out face detection on the video frame by using the deep learning model; and in response to determining that the face image is detected in the video frame, determining that the predetermined event occurs in the shooting area.
In some embodiments, the second determining unit is further configured to: in response to determining that a face image is detected in the video frame, a predetermined number of video frames including the video frame are taken as target video frames.
In some embodiments, the predetermined event is detection of disappearance of the target item; and the first determination unit is further configured to: and matching the video frame with the previous video frame in the acquired video, and determining whether the target object in the shooting area disappears or not based on the matching result.
In some embodiments, the determining whether the target item in the shooting area disappears based on the matching result includes: and determining whether the target object in the shooting area disappears or not according to the data and the matching result acquired by the weight sensor, wherein the weight sensor is arranged in the shooting area and is used for acquiring the weight information of the object in the shooting area.
In some embodiments, the second determining unit is further configured to: and in response to determining that the target object in the shooting area disappears, taking a predetermined number of video frames including the video frame as target video frames.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including: one or more processors; a storage device, on which one or more programs are stored, which, when executed by the one or more processors, cause the one or more processors to implement the method as described in any implementation manner of the first aspect.
In a fourth aspect, the disclosed embodiments provide a computer-readable medium on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method as described in any implementation manner of the first aspect.
In a fifth aspect, an embodiment of the present application provides another electronic device, including: an interface; a memory having one or more programs stored thereon; and one or more processors, operatively connected to the interface and the memory, for: collecting a video of a shooting area; transmitting the collected video to a pre-integrated visual processor, so that the visual processor executes the following operation steps: determining whether a predetermined event occurs in the shooting area based on the acquired video; determining a target video frame from the acquired video in response to determining that a predetermined event occurs in the shooting area; and storing the target video frame and sending the target video frame.
In a sixth aspect, embodiments of the present application provide a computer-readable storage medium having a computer program stored thereon, where the computer program, when executed by one or more processors, causes the one or more processors to: collecting a video of a shooting area; transmitting the collected video to a pre-integrated visual processor, so that the visual processor executes the following operation steps: determining whether a predetermined event occurs in the shooting area based on the acquired video; determining a target video frame from the acquired video in response to determining that a predetermined event occurs in the shooting area; and storing the target video frame and sending the target video frame.
The method and the device for sending information provided by the embodiment of the disclosure collect videos of shooting areas, and transmit the collected videos to a pre-integrated visual processor, so that the visual processor executes the following operations: whether a preset event occurs in a shooting area is determined based on the collected video, if the preset event occurs in the shooting area, a target video frame is determined from the collected video, and the determined target video frame is stored and sent, so that the target video frame is stored and sent when the preset event occurs in the shooting area, and the flexibility of video processing is improved.
Drawings
Other features, objects and advantages of the disclosure will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture diagram in which one embodiment of the present disclosure may be applied;
FIG. 2 is a flow diagram for one embodiment of a method for transmitting information, according to the present disclosure;
FIG. 3 is a schematic illustration of a data processing flow of a method for transmitting information according to the present disclosure;
FIG. 4 is a flow diagram of yet another embodiment of a method for transmitting information according to the present disclosure;
FIG. 5 is a schematic block diagram illustrating one embodiment of an apparatus for transmitting information according to the present disclosure;
FIG. 6 is a schematic block diagram of a computer system suitable for use in implementing an electronic device of an embodiment of the present disclosure.
Detailed Description
The present disclosure is described in further detail below with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 illustrates an exemplary system architecture 100 of a method for transmitting information or an apparatus for transmitting information to which embodiments of the present disclosure may be applied.
As shown in fig. 1, the system architecture 100 may include cameras 101, 102, a display device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the cameras 101, 102 and the display device 103, and between the cameras 101, 102 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The cameras 101, 102 may have a Vision processor (VPU, not shown) integrated therein. Various deep learning models for processing video and/or images may be run in the vision processor. In this way, the vision processor can process the video captured by the cameras 101, 102 in real time. For example, the visual processor may be a visual arithmetic chip. The visual operation chip can be used for various processing of the video.
The display device 103 may communicate with the cameras 101 and 102 through a USB (Universal Serial Bus) interface, and display information transmitted by the cameras 101 and 102. The display device 103 may be a variety of electronic devices having a display screen including, but not limited to, a display, a smart phone, a tablet computer, a laptop portable computer, a desktop computer, and the like.
The server 105 may be a server that provides various services, such as a background server that processes target video frames transmitted on the cameras 101, 102. The background server can analyze and process the received target video frame.
The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server 105 is software, it may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.
It should be understood that the number of cameras, display devices, networks, and servers in fig. 1 are merely illustrative. There may be any number of cameras, display devices, networks, and servers, as desired for implementation.
It should be noted that the method for sending information provided by the embodiment of the present disclosure is generally executed by the cameras 101 and 102, and accordingly, the apparatus for sending information is generally disposed in the cameras 101 and 102.
With continued reference to fig. 2, a flow 200 of one embodiment of a method for transmitting information in accordance with the present disclosure is shown. The method for transmitting information comprises the following steps:
In the present embodiment, the execution subject of the method for transmitting information (e.g., the cameras 101, 102 shown in fig. 1) can capture video of the shooting area in real time. The shooting area is an area where the execution subject can shoot. In practice, the orientation of the camera can be adjusted according to actual needs, so that the camera can acquire videos of a preset shooting area.
In the present embodiment, the visual processor may be integrated in advance in the execution main body. In practice, the vision processor may run various deep learning models for processing video and/or images according to actual needs. In this way, the vision processor may be used to perform various processing on the video. For example, the vision processor may perform feature extraction, face detection, face recognition, and the like on video frames in the video. In practice, the processing function implemented by the visual processor can be set according to the actual application scenario. The executing subject may transmit the captured video to the vision processor, so that the vision processor may perform the following operation steps 2021 to 2022.
At step 2021, it is determined whether a predetermined event has occurred in the shooting area based on the acquired video.
In the present embodiment, the vision processor may determine whether a predetermined event occurs in the photographing region based on the acquired video. In practice, the predetermined event may be set according to an actual application scenario. As an example, in an application scenario of security monitoring, the predetermined event may be set to detect a moving human body. As another example, in the application scenario of people flow monitoring, the predetermined event may be set to people flow greater than a preset threshold.
In the present embodiment, if it is determined that a predetermined event occurs within the photographing region, the vision processor may determine one or more video frames as target video frames from the acquired video. As an example, the vision processor may take, as the target video frame, a video frame acquired when it is determined that a predetermined event has occurred in the photographing region.
In some optional implementations of the present embodiment, the predetermined event is detection of a face image. The vision processor may be run with a deep learning model for face detection. And the step 2021 may be specifically performed as follows:
Firstly, for a video frame in an acquired video, a deep learning model is used for carrying out face detection on the video frame.
In this implementation, for each video frame in the acquired video, the visual processor may perform face detection on the video frame using the deep learning model it runs on. The vision processor may determine whether the video frame includes a face image according to the face detection result.
Then, in response to determining that a face image is detected in the video frame, it is determined that a predetermined event has occurred in the photographing region.
In this implementation, if it is determined that a face image is detected in the video frame, the vision processor may determine that a predetermined event has occurred in the photographing region.
In some alternative implementations, the step 2022 may specifically be performed as follows: in response to determining that a face image is detected in the video frame, a predetermined number of video frames including the video frame are taken as target video frames.
In this implementation, if it is determined that a face image is detected in the video frame, the vision processor may take a predetermined number of video frames including the video frame in the acquired video as target video frames. For example, the vision processor may take the video frame, a set number of video frames before the video frame (e.g., the first 5 frames), and a set number of video frames after the video frame (e.g., the last 5 frames) as the target video frame.
And step 203, storing the target video frame and sending the target video frame.
In this embodiment, the executing entity may store the target video frame determined by the vision processor. Meanwhile, the executing subject may transmit the target video frame determined by the vision processor. In practice, the target video frame can be sent to a preset receiver according to the requirements of the actual application scene.
In some optional implementations of this embodiment, the sending of the target video frame in step 203 may specifically be performed as follows: and sending the target video frame to a cloud end for processing by the cloud end.
In this implementation, the execution subject may send the target video frame determined by the visual processor to the cloud for storage and/or predetermined processing by the cloud.
In some optional implementations of this embodiment, the sending of the target video frame in step 203 may specifically be performed as follows: and sending the target video frame through a preset USB interface so as to be displayed by a display device communicated with the USB interface.
In this implementation, the execution main body may be preset with a USB interface, and the preset USB interface may communicate with the display device. In this way, the executing body may send the target video frame determined by the vision processor to the display device through the preset USB interface for display by the display device.
With continued reference to fig. 3, fig. 3 is a schematic diagram of a data processing flow of the method for transmitting information according to the present embodiment. In the data processing flow of fig. 3, the camera collects the video of the shooting area in real time, and transmits the collected video to a vision processor (not shown in the figure) integrated in advance, so that the vision processor can perform the following operations: whether a predetermined event occurs in the photographing region is determined based on the acquired video, and if it is determined that the predetermined event occurs in the photographing region, a target video frame is determined from the acquired video. And then, the camera can store the target video frame and can transmit the target video frame.
The method provided by the embodiment of the disclosure realizes the storage and the transmission of the target video frame when the predetermined event occurs in the shooting area, and improves the flexibility of video processing.
With further reference to fig. 4, a flow 400 of yet another embodiment of a method for transmitting information is shown. The process 400 of the method for transmitting information includes the steps of:
In this embodiment, step 401 is similar to step 201 of the embodiment shown in fig. 2, and is not described here again.
In the present embodiment, the visual processor may be integrated in advance in the execution main body. The vision processor may be used to perform various processing on the video and/or images. For example, the vision processor may determine whether items in the shooting area have changed, e.g., determine whether the number, location, etc. of the items have changed, based on the acquired video. Here, the execution main body may be applied to an unmanned store in which at least one kind of items, each of which may be at least one, may be stored. The photographing area may be a shelf for storing items in the unmanned store.
In this embodiment, for each video frame in the acquired video, the vision processor may match the video frame with a previous video frame, and determine whether the target item in the shooting area disappears according to the matching result. For example, the vision processor may extract feature information of the video frame and the previous video frame, respectively, and determine whether the target object in the shooting area disappears according to a comparison between the feature information of the video frame and the previous video frame. If the predetermined event is disappeared, it is determined that the predetermined event occurs in the photographing region. Here, the predetermined event may refer to disappearance of the target item.
In some optional implementations of this embodiment, the determining whether the target item in the shooting area disappears based on the matching result in step 4021 may specifically be performed as follows: and determining whether the target object in the shooting area disappears or not according to the data collected by the weight sensor and the matching result.
In this implementation, a weight sensor may be disposed in the shooting area, and the weight sensor may be configured to collect weight information, e.g., a weight value, of an article in the shooting area. The weight sensor may send weight information collected in real time to the vision processor. In this way, the vision processor can determine whether the target object in the shooting area disappears according to the information collected by the weight sensor and the matching result in step 4021. As an example, a target weight value for the target item may be pre-stored in the vision processor. In this way, if the weight value acquired by the weight sensor at the present time is decreased from the weight value acquired at the previous time by the same weight value as the target weight value, the vision processor may determine that the target item within the photographing region is disappeared. Here, if the vision processor determines that the target item within the photographing area disappears based on the weight sensor and/or the matching result, it may be determined that the target item within the photographing area disappears.
In this embodiment, if it is determined that the target item within the shooting area disappears, the vision processor may regard, as the target video frame, a predetermined number of video frames including the video frame in the acquired video. For example, the vision processor may take the video frame, a set number of video frames before the video frame (e.g., the first 5 frames), and a set number of video frames after the video frame (e.g., the last 5 frames) as the target video frame.
And step 403, storing the target video frame and sending the target video frame.
In this embodiment, step 403 is similar to step 203 of the embodiment shown in fig. 2, and is not described herein again.
As can be seen from fig. 4, compared with the embodiment corresponding to fig. 2, the flow 400 of the method for sending information in the present embodiment highlights the step of determining the target video frame when determining that the target item in the shooting area disappears. Therefore, the scheme described in the embodiment can store and send the target video frame when the target object in the shooting area disappears, so that the target video frame is stored and sent while the target object in the shooting area is monitored by the camera, and the flexibility of video processing is improved.
With further reference to fig. 5, as an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of an apparatus for sending information, which corresponds to the method embodiment shown in fig. 2, and which is particularly applicable in various electronic devices.
As shown in fig. 5, the apparatus 500 for transmitting information of the present embodiment includes: the device comprises an acquisition unit 501, an execution unit 502 and a sending unit 503. The acquisition unit 501 is configured to acquire a video of a shooting area; the execution unit 502 is configured to transmit the captured video to a pre-integrated vision processor for the vision processor to perform preset operation steps, wherein the vision processor includes: a first determination unit (not shown in the figure) configured to determine whether a predetermined event has occurred in the above-mentioned shooting area based on the acquired video; a second determination unit (not shown in the figure) configured to determine a target video frame from the acquired video in response to a determination that a predetermined event has occurred in the above-mentioned shooting area; the transmitting unit 503 is configured to store the target video frame and transmit the target video frame.
In this embodiment, specific processing of the acquisition unit 501, the execution unit 502, and the sending unit 503 of the apparatus 500 for sending information and technical effects brought by the processing can refer to related descriptions of step 201, step 202, and step 203 in the corresponding embodiment of fig. 2, which are not described herein again.
In some optional implementations of this embodiment, the sending unit 503 is further configured to: and sending the target video frame to a cloud end for processing by the cloud end.
In some optional implementations of this embodiment, the sending unit 503 is further configured to: and sending the target video frame through a preset USB interface so as to be displayed by a display device communicated with the USB interface.
In some optional implementations of this embodiment, the predetermined event is detection of a face image, and the visual processor runs a deep learning model for face detection; and the first determination unit, further configured to: for a video frame in the acquired video, carrying out face detection on the video frame by using the deep learning model; and in response to determining that the face image is detected in the video frame, determining that the predetermined event occurs in the shooting area.
In some optional implementations of this embodiment, the second determining unit is further configured to: in response to determining that a face image is detected in the video frame, a predetermined number of video frames including the video frame are taken as target video frames.
In some optional implementations of this embodiment, the predetermined event is detection of disappearance of the target item; and the first determination unit is further configured to: and matching the video frame with the previous video frame in the acquired video, and determining whether the target object in the shooting area disappears or not based on the matching result.
In some optional implementations of this embodiment, the determining whether the target item in the shooting area disappears based on the matching result includes: and determining whether the target object in the shooting area disappears or not according to the data and the matching result acquired by the weight sensor, wherein the weight sensor is arranged in the shooting area and is used for acquiring the weight information of the object in the shooting area.
In some optional implementations of this embodiment, the second determining unit is further configured to: and in response to determining that the target object in the shooting area disappears, taking a predetermined number of video frames including the video frame as target video frames.
Referring now to FIG. 6, a schematic diagram of an electronic device (e.g., cameras 101, 102 of FIG. 1) 600 suitable for use in implementing embodiments of the present disclosure is shown. The camera shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 6, electronic device 600 may include a processing means (e.g., central processing unit, graphics processor, vision processor, etc.) 601 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage means 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the electronic apparatus 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Generally, the following devices may be connected to the I/O interface 605: an input Device 606 including, for example, a CCD image sensor (charged Device), a weight sensor, or the like; output devices 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, flash memory cards; and a communication device 609. The communication means 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 illustrates an electronic device 600 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 6 may represent one device or may represent multiple devices as desired.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 609, or may be installed from the storage means 608, or may be installed from the ROM 602. The computer program, when executed by the processing device 601, performs the above-described functions defined in the methods of embodiments of the present disclosure.
It should be noted that the computer readable medium described in the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In embodiments of the present disclosure, however, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: collecting a video of a shooting area; transmitting the collected video to a pre-integrated visual processor, so that the visual processor executes the following operation steps: determining whether a predetermined event occurs in the shooting area based on the acquired video; determining a target video frame from the acquired video in response to determining that a predetermined event occurs in the shooting area; and storing the target video frame and sending the target video frame.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, an execution unit, and a transmission unit. The names of the units do not in some cases constitute a limitation on the units themselves, and for example, the capturing unit may also be described as a "unit that captures a video of a shooting area".
As another aspect, an embodiment of the present application further provides another server, including: an interface; a memory having one or more programs stored thereon; and one or more processors, operatively connected to the interface and the memory, for: collecting a video of a shooting area; transmitting the collected video to a pre-integrated visual processor, so that the visual processor executes the following operation steps: determining whether a predetermined event occurs in the shooting area based on the acquired video; determining a target video frame from the acquired video in response to determining that a predetermined event occurs in the shooting area; and storing the target video frame and sending the target video frame.
As another aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by one or more processors, the one or more processors are caused to: collecting a video of a shooting area; transmitting the collected video to a pre-integrated visual processor, so that the visual processor executes the following operation steps: determining whether a predetermined event occurs in the shooting area based on the acquired video; determining a target video frame from the acquired video in response to determining that a predetermined event occurs in the shooting area; and storing the target video frame and sending the target video frame.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (18)
1. A method for transmitting information, comprising:
collecting a video of a shooting area;
transmitting the collected video to a pre-integrated vision processor, so that the vision processor can execute the following operation steps: determining whether a predetermined event occurs in the photographing region based on the acquired video; determining a target video frame from the acquired video in response to determining that a predetermined event occurs in the shooting area;
and storing the target video frame, and sending the target video frame.
2. The method of claim 1, wherein the transmitting the target video frame comprises:
And sending the target video frame to a cloud end for processing by the cloud end.
3. The method of claim 1, wherein the transmitting the target video frame comprises:
and sending the target video frame through a preset USB interface so as to be displayed by a display device communicated with the USB interface.
4. The method of claim 1, wherein the predetermined event is the detection of a face image, the vision processor running a deep learning model for face detection; and
the determining whether a predetermined event occurs in the photographing region based on the acquired video includes:
for a video frame in the obtained video, carrying out face detection on the video frame by using the deep learning model; and in response to determining that the face image is detected in the video frame, determining that a predetermined event occurs in the shooting area.
5. The method of claim 4, wherein said determining a target video frame from the acquired video in response to determining that a predetermined event occurred in the capture area comprises:
in response to determining that a face image is detected in the video frame, a predetermined number of video frames including the video frame are taken as target video frames.
6. The method of claim 1, wherein the predetermined event is detection of disappearance of the target item; and
the determining whether a predetermined event occurs in the photographing region based on the acquired video includes:
and matching the video frame with the previous video frame in the acquired video, and determining whether the target object in the shooting area disappears or not based on the matching result.
7. The method of claim 6, wherein the determining whether the target item within the photographing area disappears based on the matching result comprises:
and determining whether the target object in the shooting area disappears or not according to the data and the matching result acquired by the weight sensor, wherein the weight sensor is arranged in the shooting area and used for acquiring the weight information of the object in the shooting area.
8. The method of claim 6, wherein said determining a target video frame from the captured video in response to determining that a predetermined event occurred in the capture area comprises:
in response to determining that the target item within the shooting area disappears, a predetermined number of video frames including the video frame are taken as target video frames.
9. An apparatus for transmitting information, comprising:
a capture unit configured to capture a video of a shooting area;
an execution unit configured to transmit the captured video to a pre-integrated vision processor for the vision processor to perform preset operation steps, wherein the vision processor comprises: a first determination unit configured to determine whether a predetermined event has occurred in the photographing region based on the acquired video; a second determination unit configured to determine a target video frame from the acquired video in response to determining that a predetermined event has occurred in the photographing region;
a transmitting unit configured to store the target video frame and transmit the target video frame.
10. The apparatus of claim 9, wherein the transmitting unit is further configured to:
and sending the target video frame to a cloud end for processing by the cloud end.
11. The apparatus of claim 9, wherein the transmitting unit is further configured to:
and sending the target video frame through a preset USB interface so as to be displayed by a display device communicated with the USB interface.
12. The apparatus of claim 9, wherein the predetermined event is detection of a face image, the vision processor running a deep learning model for face detection; and
The first determination unit is further configured to:
for a video frame in the obtained video, carrying out face detection on the video frame by using the deep learning model; and in response to determining that the face image is detected in the video frame, determining that a predetermined event occurs in the shooting area.
13. The apparatus of claim 12, wherein the second determining unit is further configured to:
in response to determining that a face image is detected in the video frame, a predetermined number of video frames including the video frame are taken as target video frames.
14. The apparatus of claim 9, wherein the predetermined event is detection of disappearance of the target item; and
the first determination unit is further configured to:
and matching the video frame with the previous video frame in the acquired video, and determining whether the target object in the shooting area disappears or not based on the matching result.
15. The apparatus of claim 14, wherein the determining whether the target item within the photographing area disappears based on the matching result comprises:
and determining whether the target object in the shooting area disappears or not according to the data and the matching result acquired by the weight sensor, wherein the weight sensor is arranged in the shooting area and used for acquiring the weight information of the object in the shooting area.
16. The apparatus of claim 14, wherein the second determining unit is further configured to:
in response to determining that the target item within the shooting area disappears, a predetermined number of video frames including the video frame are taken as target video frames.
17. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-8.
18. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-8.
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