JPWO2010137104A1 - Video processing apparatus, video processing method, and video processing program - Google Patents

Abstract

The video processing apparatus includes a video sickness scene detection unit and a video processing unit. The video sickness scene detecting means detects a scene in which video sickness occurs from the video data composed of a plurality of image frames when the video data is reproduced. The video processing means performs scene processing based on the detection result of the video sickness scene detection means.

Description

  The present invention relates to a video processing technique for detecting and processing a specific scene from video data shot by a moving body.

  2. Description of the Related Art Conventionally, there is a technique for processing a moving image (video data) including a plurality of captured image frames in accordance with the purpose. For example, Patent Document 1 discloses a technique for adjusting the reproduction speed of a moving image by adjusting the number of frames to be reproduced or recorded in accordance with the acceleration at the time of moving image shooting.

JP 2006-262135 A

  In general, when viewing video data acquired by an in-vehicle camera such as a drive recorder, a sense of incongruity may occur due to shaking of a moving body, and video sickness may occur. Here, “video sickness” refers to symptoms such as nausea, dizziness, headache, and eye strain caused by watching video. Image sickness occurs mainly due to moving visual stimuli. Therefore, in the above-described case, in order to prevent viewers from getting sick of video, it is necessary to appropriately process video data captured from a moving body. In Patent Document 1, the above problem is not studied at all.

  The present invention has been made to solve the above-described problems, and an object thereof is to apply a video processing apparatus capable of appropriately processing video data in order to suppress video sickness during playback. And

  According to the first aspect of the present invention, the video processing apparatus includes a video sickness scene detecting unit that detects a scene in which video sickness occurs when the video data is reproduced from video data composed of a plurality of image frames, and the video sickness scene. Video processing means for processing the scene based on the detection result of the detection means.

  According to a fourteenth aspect of the present invention, there is provided a video sickness scene detection step in which the video processing device detects a scene in which video sickness occurs during reproduction of the video data from video data composed of a plurality of image frames, and the video sickness scene. An image processing step of processing the scene based on the detection result of the detection means.

  The invention according to claim 15 is a video processing program executed by a computer, wherein the video sickness scene detection detects a scene in which video sickness occurs during reproduction of the video data from video data composed of a plurality of image frames. And video processing means for processing the scene based on the detection result of the video sickness scene detection means.

It is a schematic block diagram of the video processing system which concerns on each Example of this invention. It is an example of the navigation apparatus structure to which the video processing apparatus which concerns on this invention is applied. 1 is a functional block diagram of a video processing system according to a first embodiment. It is an example of a map of the absolute value of the acceleration As and the processing degree P, and a map of the video speed magnification and the processing degree P. It is an example of the graph which shows the change of the acceleration As with time passage. It is an example of the flowchart which shows the process sequence of 1st Example. It is a part of functional block diagram of the video processing apparatus which concerns on the modification 2 of 1st Example. It is a part of functional block diagram of the video processing system which concerns on 2nd Example. The conceptual diagram of the radius R which the video processing apparatus concerning 2nd Example uses, and an example of the map of the reciprocal number of the radius R and the process degree P are shown. It is an example of the flowchart which shows the process sequence of 2nd Example. It is a functional block diagram of the video processing system which concerns on 3rd Example. It is a functional block diagram of the video processing system which concerns on 4th Example. It is a functional block diagram of the video processing system which concerns on 5th Example.

  In one aspect of the present invention, the video processing apparatus includes: a video sickness scene detection unit that detects a scene in which video sickness occurs when the video data is reproduced from video data including a plurality of image frames; and the video sickness scene detection. Image processing means for processing the scene based on the detection result of the means.

  The video processing apparatus includes video sickness scene detection means and video processing means. The video sickness scene detection means detects a scene in which video sickness occurs when the video data is reproduced from the video data composed of a plurality of image frames. Here, the “scene where video sickness occurs” specifically refers to one or a plurality of continuous image frames corresponding to a video causing video sickness. The video processing means performs scene processing based on the detection result of the video sickness scene detection means. Here, the “detection result” is not limited to information related to the presence or absence of a video sickness scene, and may include information related to the degree of video sickness, for example. In this way, the video processing apparatus can appropriately convert the video data into video data that does not cause video sickness.

  In another aspect of the above video processing device, the video sickness scene detecting means has a higher probability of video sickness and a higher degree of video sickness as the video change during reproduction of the video data is larger. to decide. In general, it is known that video sickness occurs as the video changes more severely. Therefore, by doing in this way, the video sickness scene detection means can detect the scene where video sickness occurs appropriately.

  In another aspect of the video processing device, the video data is taken from an imaging device mounted on a moving body, and the video sickness scene detection unit temporally corresponds to the video data. The scene is detected based on information on the behavior of the moving object. Here, the “information regarding the behavior of the moving object” corresponds to detection values of various sensors included in the moving object such as a detection value of an acceleration sensor, a detection value of a gyroscope, a detection value of a GPS (Global Positioning System), and the like. To do. Further, “corresponding in terms of time” means that the shooting time of the video data and the time when the above-described sensor detects the behavior of the moving body substantially coincide. In this way, the video sickness scene detection unit can appropriately detect the video sickness scene by paying attention to the fact that the behavior of the moving body affects the imaging environment of the imaging device.

  In another aspect of the video processing device, the video sickness scene detection unit detects the scene based on acceleration in a side surface direction of the moving body. Here, the “side surface direction” refers to a direction that is substantially perpendicular to the traveling direction of the moving body and is substantially parallel to the travel route. Therefore, in this aspect, the video sickness scene detection means can appropriately detect the video data generated when the imaging environment of the imaging device is not stable, such as when the moving body is running on a curve, as a video sickness scene.

  In another aspect of the video processing apparatus, the video sickness scene detection unit determines that video motion sickness does not occur in video data corresponding to the time when the moving body is stopped. Generally, it is considered that video sickness does not occur in video data taken when a moving body is stopped. On the other hand, for example, when the moving body stops on a slope having an inclination in the side surface direction, the acceleration in the side direction of the moving body acquired from the acceleration sensor increases according to the inclination even when the moving body is stopped. Therefore, even in this case, the video sickness scene detection means can prevent erroneous determination of video data taken when the moving body is stopped as a video sickness scene.

  In another aspect of the video processing apparatus, the video sickness scene detection unit determines whether or not the moving body is at a stop based on the speed of the moving body and / or the acceleration of the moving body. By doing in this way, the video sickness scene detection means can appropriately determine whether or not the moving body is stopped.

  In another aspect of the video processing device, the scene is detected based on a curvature of a traveling route of the moving body. In general, video data shot while traveling on a curve with a large degree of bending of the travel route of a mobile object is likely to cause video sickness. Therefore, the video processing apparatus can appropriately detect a video sickness scene based on the curvature of the travel route.

  In another aspect of the video processing apparatus, the video sickness scene detection unit detects the scene based on acceleration in the traveling direction of the moving body. In general, video shot during sudden acceleration / deceleration tends to cause video sickness. Therefore, in this aspect, the video sickness scene detection means regards the video data as a video sickness scene when, for example, the absolute value of the acceleration in the traveling direction is a predetermined value or more. In this case, the predetermined value is set to an appropriate value based on experiments or the like.

  In another aspect of the video processing apparatus, the video sickness scene detection unit detects the scene based on an inclination in a traveling direction of a travel route of the moving body. In general, video shot while traveling uphill or downhill is likely to cause video sickness. Therefore, the video sickness scene detection means can detect the video sickness scene appropriately by grasping the inclination based on the position information and map information by GPS.

  In another aspect of the video processing device, the video sickness scene detection unit calculates a processing degree indicating a degree to be processed by the video processing unit, and the video processing unit increases the processing degree, The reproduction speed of the video data corresponding to the processing degree in time is set small. In general, video sickness is reduced by reducing the playback speed of the video data. Accordingly, the video processing means can appropriately process the video sickness scene by reducing the reproduction speed of the video data by interpolating a frame with the video data as the degree of processing increases.

  In another aspect of the video processing apparatus, the video sickness scene detection unit calculates a processing level indicating a level to be processed by the video processing unit, and the video processing unit has the processing level as a first threshold value. In the above case, the display size of the video data corresponding temporally to the processing degree is reduced. The first threshold value is set to an appropriate value based on experiments or the like. In general, video sickness is reduced by reducing the display size of video data. Therefore, the video processing means can appropriately prevent video sickness during playback by reducing the display size of video data whose processing degree is larger than the first threshold.

  In another aspect of the video processing apparatus, the video sickness scene detection unit calculates a processing level indicating a level to be processed by the video processing unit, and the video processing unit has a second threshold value for the processing level. In the above case, the frames constituting the video data corresponding temporally to the processing degree are deleted. The second threshold is set to an appropriate value based on experiments or the like. In this way, the video processing means can reliably prevent video sickness during playback by deleting a portion that has a high degree of processing, that is, that is highly likely to cause video sickness.

  In another aspect of the video processing apparatus, a video sickness scene detection step of detecting a scene in which video sickness occurs during reproduction of the video data from video data composed of a plurality of image frames, and the video sickness scene detection means And an image processing step for processing the scene based on the detection result. By using this method, the video processing apparatus can appropriately convert the video data into video data that does not cause video sickness.

  In still another aspect of the above video processing device, the video processing program is executed by a computer, and detects a scene in which video sickness occurs when video data is reproduced from video data composed of a plurality of image frames. A sickness scene detection means; and a video processing means for processing the scene based on a detection result of the video sickness scene detection means. By installing the above-described program, the video processing apparatus can appropriately convert the video data into video data that does not cause video sickness. In a preferred example, the above program is stored in a storage medium.

  Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

[Overview]
First, prior to the description of each embodiment to be described later, an outline of a video processing apparatus according to the present invention will be described with reference to FIG.

  FIG. 1 is a schematic configuration diagram of a video processing system according to the present invention. As shown in FIG. 1, the video processing system includes a video processing device 100, a video input device 200, and a video output device 300. The video processing system is mounted on a moving body such as a vehicle. Hereinafter, the video processing system will be described as being mounted on a vehicle as an example.

  The video input device 200 includes an imaging device installed in a vehicle, video data Sv composed of a plurality of image frames previously captured by the imaging device, and detection values of various sensors detected during imaging (hereinafter, “ It functions as a recording device that holds the sensor value Se ”. The various sensors described above will be described later.

  The video processing device 100 is electrically connected to the video input device 200 and the video output device 300. The video processing device 100 receives the video data Sv from the video input device 200, and also the video data Sv based on the sensor value Se from various sensors mounted on the vehicle or the sensor value Se supplied from the video input device. A portion where video sickness occurs (hereinafter referred to as “video sickness scene”) is identified. The video processing apparatus 100 generates video data that does not cause video sickness by processing the video sickness scene (hereinafter referred to as “processed video data Svr”), and uses the processed video data Svr as a video recording device. 300. The video processing apparatus 100 includes a video sickness scene detection unit 1 and a video processing unit 2.

  The video sickness scene detection unit 1 identifies a video sickness scene in the video data Sv by analyzing the behavior of the vehicle or the video data Sv. Specifically, the motion sickness scene detection unit 1 detects a curve (that is, a travel route having a curvature equal to or greater than a predetermined value) based on the sensor value Se, and / or detects whether there is a sudden acceleration / deceleration of the vehicle, travel A change in the inclination of the route is detected, and the video data Sv corresponding to the change is specified as a video sickness scene. In addition, the video sickness scene detection unit 1 determines the degree of processing (hereinafter referred to as “processing degree P”) performed by the video processing unit 2 on the detected video sickness scene.

More specifically, for example, the video sickness scene detection unit 1 detects a curve and determines the processing degree P based on one or a plurality of information arbitrarily combined among the following information.
・ Vehicle angular velocity calculated based on detection values of the rudder angle sensor and vehicle speed sensor
-Vehicle location information specified based on GPS or predetermined map information
・ Vehicle angular velocity calculated based on detected value of gyroscope
・ Acceleration in the front-rear direction or side (left-right) direction of the vehicle acquired from the acceleration sensor
-Parameters obtained by performing image processing on each frame constituting the video data Sv, and other information obtained by performing image processing on the video data Sv. A method for detecting a curve based on these information and the processing degree P A specific example of calculating the value will be described in detail in an example described later.

  The motion sickness scene detection unit 1 detects the presence or absence of sudden acceleration / deceleration of the vehicle based on, for example, the detection value of the acceleration sensor and / or the detection value of the vehicle speed sensor. Here, “rapid acceleration / deceleration” refers to, for example, a case where the absolute value of the acceleration in the lateral direction or the front-rear direction of the vehicle has reached a predetermined value or more. The predetermined value is set to an appropriate value based on experiments or the like.

Furthermore, the video sickness scene detection unit 1, for example, abruptly changes in the inclination angle of the travel route of the travel route (for example, starts to rise and starts to fall) based on one or a plurality of information arbitrarily combined among the following information Is detected.
・ The inclination of the vehicle in the longitudinal direction calculated based on the detection value of a gyroscope, etc.
・ Altitude calculated based on GPS or predetermined map information
-Parameters obtained by image processing of each frame constituting the video data Sv, and other information obtained by image processing of the video data Sv The video processing unit 2 is supplied from the video sickness scene detection unit 1 The video data Sv is processed based on the processing degree P. For example, the video processing unit 2 sets the speed at which the video sickness scene is reproduced (hereinafter referred to as “video speed”) by performing frame thinning or frame interpolation on the video sickness scene according to the processing degree P. Change). As another example, the video processing unit 2 reduces the image size according to the processing degree P for each frame of the video sickness scene. As yet another example, the video processing unit 2 deletes a frame corresponding to a video sickness scene portion. The video processing unit 2 can generate post-processing video data Svr in which video sickness does not occur by selecting and executing one or more of these methods.

  The video output device 300 functions as a display device that displays the processed video data Svr supplied from the video processing device 100 on a display or the like, and / or a video recording device that records the processed video data Svr.

  In the following first to fifth embodiments, more detailed processing of the above-described video processing system will be described.

[First embodiment]
Next, the first embodiment will be described. Hereinafter, after describing a schematic configuration of a navigation device to which the video processing device 100 is applied, a video processing method, a processing flow, and each modification example executed by the video processing device 100 will be described in order.

(Outline configuration)
FIG. 2 shows an example of a schematic configuration of a navigation apparatus to which the video processing apparatus 100 is applied. As shown in FIG. 2, the navigation device includes a self-supporting positioning device 10, a GPS receiver 18, a system controller 20, a disk drive 31, a data storage unit 36, a communication interface 37, a communication device 38, a display unit 40, and an audio output unit. 50 and an input device 60. As will be described later, the video processing apparatus 100 according to the first embodiment corresponds to the CPU 22 and the acceleration sensor 11.

  The autonomous positioning device 10 includes an acceleration sensor 11, an angular velocity sensor 12, and a distance sensor 13. The acceleration sensor 11 is made of, for example, a piezoelectric element, detects acceleration in the front-rear direction and / or horizontal direction of the vehicle, and outputs acceleration data. The angular velocity sensor 12 is composed of, for example, a vibrating gyroscope, detects the angular velocity of the vehicle when the direction of the vehicle is changed, and outputs angular velocity data and relative azimuth data. The distance sensor 13 measures a vehicle speed pulse composed of a pulse signal generated with the rotation of the vehicle wheel.

  The GPS receiver 18 receives radio waves 19 carrying downlink data including positioning data from a plurality of GPS satellites. The positioning data is used to detect the absolute position of the vehicle from latitude and longitude information.

  The system controller 20 includes an interface 21, a CPU (Central Processing Unit) 22, a ROM (Read Only Memory) 23, and a RAM (Random Access Memory) 24, and controls the entire video processing apparatus 100.

  The interface 21 performs an interface operation with the acceleration sensor 11, the angular velocity sensor 12, the distance sensor 13, and the GPS receiver 18. From these, vehicle speed pulses, acceleration data, relative azimuth data, angular velocity data, GPS positioning data, absolute azimuth data, and the like are input to the system controller 20.

  The CPU 22 controls the entire system controller 20. The CPU 22 functions as the video sickness scene detection unit 1 and the video processing unit 2 described above by executing a program prepared in advance. The ROM 23 includes a nonvolatile memory (not shown) in which a control program for controlling the system controller 20 is stored. The RAM 24 stores various data such as route data preset by the user via the input device 60 so as to be readable, and provides a working area to the CPU 22.

  A system controller 20, a disk drive 31 such as a CD-ROM drive or a DVD-ROM drive, a data storage unit 36, a communication interface 37, a display unit 40, an audio output unit 50 and an input device 60 are mutually connected via a bus line 30. It is connected to the.

  The disk drive 31 reads and outputs content data such as music data and video data from a disk 33 such as a CD or DVD under the control of the system controller 20. The disk drive 31 may be either a CD-ROM drive or a DVD-ROM drive, or may be a CD and DVD compatible drive. The data storage unit 36 is configured by, for example, an HDD and stores various data used for navigation processing such as map information. The communication device 38 includes, for example, an FM tuner, a beacon receiver, a mobile phone, a dedicated communication card, and the like, and is distributed from a VICS (Vehicle Information Communication System) center or the like (hereinafter referred to as “VICS information”). Is acquired from the radio wave 39. The interface 37 performs an interface operation of the communication device 38 and inputs the VICS information to the system controller 20 or the like.

  The display unit 40 displays various display data on a display device such as a display under the control of the system controller 20. Specifically, the system controller 20 reads map data from the data storage unit 36. The display unit 40 displays the map data read from the data storage unit 36 by the system controller 20 on the display screen. The display unit 40 includes a graphic controller 41 that controls the entire display unit 40 based on control data sent from the CPU 22 via the bus line 30 and a memory such as a VRAM (Video RAM), and can display image information that can be displayed immediately. A buffer memory 42 that temporarily stores, a display control unit 43 that controls display of a display 44 such as a liquid crystal display or a CRT (Cathode Ray Tube) based on image data output from the graphic controller 41, and a display 44 are provided. . The display 44 functions as an image display unit, and includes, for example, a liquid crystal display device having a diagonal size of about 5 to 10 inches and is mounted near the front panel in the vehicle.

  The audio output unit 50 performs D / A (Digital to Analog) conversion of audio digital data sent from the CD-ROM drive 31, DVD-ROM 32, RAM 24, or the like via the bus line 30 under the control of the system controller 20. A D / A converter 51 to perform, an amplifier (AMP) 52 that amplifies the audio analog signal output from the D / A converter 51, and a speaker 53 that converts the amplified audio analog signal into sound and outputs the sound into the vehicle. It is prepared for.

The input device 60 includes keys, switches, buttons, a remote controller, a voice input device, and the like for inputting various commands and data. The input device 60 is disposed around the front panel and the display 44 of the main body of the in-vehicle electronic system mounted in the vehicle.
(Video processing method)
Next, a video processing method executed by the video processing apparatus 100 will be described. In the first embodiment, the image processing apparatus 100 detects a running curve based on the horizontal acceleration (hereinafter referred to as “acceleration As”), and uses the image data Sv captured during the running of the curve. Identified as a video sickness scene. Furthermore, the video processing apparatus 100 calculates the processing degree P based on the absolute value of the acceleration As, and sets the speed at which the video sickness scene is reproduced based on the processing degree P. Thereby, the video processing apparatus 100 appropriately generates post-processing video data Svr in which video sickness is suppressed.

  The details of the above-described processing will be described below with reference to FIG. FIG. 3 is an example of a functional block diagram of the video processing system according to the first embodiment. As shown in FIG. 3, the video processing apparatus 100 receives video data Sv from an imaging apparatus 200x that captures images in a predetermined direction from a vehicle, and processes the processed video into a video recording apparatus 300x that can record the data. Data Svr is supplied. The video processing apparatus 100 includes a horizontal direction acceleration determination unit 15, a vehicle stop determination unit 16, a curve detection unit 17, a video speed conversion unit 2 x, and an acceleration sensor 11.

  The horizontal direction acceleration determination unit 15 receives the supply of the acceleration As from the acceleration sensor 11 and calculates the processing degree P by referring to a predetermined map or expression based on the acceleration As. The above-described map or expression is created in advance based on, for example, experiments, and is stored in a memory such as the ROM 23 or the data storage unit 36.

This will be specifically described with reference to FIG. FIG. 4A is an example of a map of the processing degree P determined by the video speed conversion unit 2x and the absolute value of the acceleration As. In FIG. 4A, the processing degree P is set to a value between 0 and 1, and the closer to 1, the higher the degree at which the video data Sv should be processed by the video speed conversion unit 2x. As shown to a), the horizontal direction acceleration determination part 15 sets the process degree P large, so that the absolute value of acceleration As is large. In other words, the horizontal direction acceleration determination unit 15 has a greater degree of curvature (curvature) of the travel route as the absolute value of the acceleration As is larger, and is more severe than the degree to be processed into the video data Sv supplied from the imaging device 200x. It is determined that a video sickness scene occurs. By doing in this way, the horizontal direction acceleration determination part 15 sets the process degree P appropriately so that the video speed of the video data Sv corresponding temporally with this may become slow, so that the absolute value of acceleration As is large. be able to. The above “corresponding in time” means that the time when the acceleration sensor 11 detects the acceleration As and the time when the imaging device 200x generates the video data Sv match.

  Next, the process which the vehicle stop determination part 16 performs is demonstrated. The vehicle stop determination unit 16 determines whether or not the vehicle is stopped based on a fluctuation width (hereinafter referred to as “fluctuation width W”) of the acceleration As supplied from the acceleration sensor 11 in a predetermined time width. The determination result (hereinafter referred to as “determination result J”) is supplied to the curve detection unit 17. The predetermined time width is set to an appropriate value based on experiments or the like. Specifically, the vehicle stop determination unit 16 determines that the vehicle is stopped when the fluctuation range W is equal to or less than a predetermined threshold (hereinafter referred to as “threshold Wth”). The threshold value Wth is set based on an experiment or the like, for example, to the upper limit value of the fluctuation range W that can be considered that the vehicle is stopped.

  This will be supplementarily described. In general, when the vehicle is stopped on a slope having an inclination in the lateral direction of the vehicle, the absolute value of the acceleration As detected based on the acceleration sensor 11 increases according to the inclination due to gravity. On the other hand, the video data Sv generated from the imaging device 200x in the above-described case has little video change during reproduction because the vehicle is stopped, and video sickness does not occur. In consideration of the above, the vehicle stop determination unit 16 determines whether or not the vehicle is stopped, thereby preventing the video data Sv acquired while the vehicle is stopped on a slope from being erroneously determined as a video sickness scene. Execution of video processing can be suppressed.

  Here, the process of the vehicle stop determination part 16 mentioned above is demonstrated using the specific example shown in FIG. FIG. 5 is an example of a graph of the time change of the acceleration As in a predetermined time width. Here, the time “T0” indicates the time when the vehicle is stopped, the time “T1” indicates the time when the vehicle is started from the stop state, and the time “T2” indicates the time when the vehicle is traveling.

  As shown in FIG. 5, the acceleration As hardly changes from the time T0 to the time T1 due to the vehicle being stopped. Accordingly, the fluctuation width W during this period is equal to or smaller than the predetermined width “W0” which is smaller than the threshold value Wth. Therefore, in this period, the vehicle stop determination unit 16 determines that the vehicle is stopped.

  On the other hand, during the period from time T1 to time T2, the acceleration As varies due to the start of the vehicle. As a result, the fluctuation width W changes in the vicinity of the predetermined width “W1” that is larger than the threshold value Wth. Therefore, in this period, the vehicle stop determination unit 16 determines that the vehicle is not stopped.

  As described above, the vehicle stop determination unit 16 can determine whether or not the vehicle is appropriately stopped based on the fluctuation range W.

  Next, processing executed by the curve detection unit 17 will be described. The curve detection unit 17 determines whether or not the vehicle is traveling on a curve based on the determination result J supplied from the vehicle stop determination unit 16 and based on the processing degree P supplied from the horizontal acceleration determination unit 15. Control the video speed. Specifically, when the curve detection unit 17 determines that the vehicle is not stopped based on the determination result J, the curve detection unit 17 estimates the processing degree P supplied from the horizontal acceleration determination unit 15 as the degree of curve of the travel route curve. And supplied to the video speed converter 2x.

  On the other hand, when the curve detection unit 17 determines that the vehicle is stopped based on the determination result J, the processing degree P supplied from the horizontal acceleration determination unit 15 is set to a value that does not process the video data Sv (that is, 0). To do. As a result, the curve detection unit 17 can suppress unnecessary processing of the video data Sv while the vehicle is stopped, in which a video sickness scene does not actually occur.

  Next, processing executed by the video speed conversion unit 2x will be described. The video speed conversion unit 2x refers to a predetermined map or expression based on the processing degree P supplied from the curve detection unit 17, so that a dummy frame between the frames of the video data Sv supplied from the imaging device 200x, For example, the video data Sv is interpolated by inserting copies of frames before and after the insertion position. The above-described map or formula is created based on experiments or the like and is stored in the ROM 23 or the data storage unit 36.

  A specific example of this will be described with reference to FIG. FIG. 4B is an example of a map of the processing degree P and the video speed magnification corresponding thereto (hereinafter referred to as “video speed magnification”). As shown in FIG. 4B, the video speed conversion unit 2x decreases the video speed magnification as the processing degree P increases. Specifically, the video speed conversion unit 2x decreases the interval at which the dummy frame is inserted as the processing degree P increases. By doing in this way, the video speed conversion unit 2x decreases the video speed and suppresses the occurrence of video sickness at the time of reproduction for a video scene having a high probability of video sickness.

  Then, the video speed conversion unit 2x supplies the processed video data Svr to the video recording device 300x. The video recording device 300x stores the supplied processed video data Svr in a memory.

  When the processing degree P supplied from the curve detection unit 17 is supplied later than the video data Sv corresponding to the time, the video speed conversion unit 2x stores the video data Sv for a predetermined time width, for example. Processed later. The predetermined time width is set based on, for example, experiments on the above-described delay time width. Accordingly, the video speed conversion unit 2x can process the processing degree P and the video data Sv to be processed based on the processing degree P in an appropriate manner.

(Processing flow)
Next, a processing procedure executed by the video processing apparatus 100 in the first embodiment will be described with reference to FIG. FIG. 6 is an example of a flowchart showing a processing procedure executed by the video processing apparatus 100 in the first embodiment. The video processing apparatus 100 repeatedly executes the process of the flowchart shown in FIG. 6 according to a predetermined cycle.

  First, the video processing apparatus 100 detects the acceleration As (step S101). Specifically, the video processing device 100 determines the acceleration As based on the detection value from the acceleration sensor 11.

  Then, the video processing device 100 determines whether or not the fluctuation range W is larger than the threshold value Wth (step S102). Specifically, the video processing apparatus 100 calculates the fluctuation range W based on a predetermined number of samples of the acceleration As acquired immediately before and compares the fluctuation range W with the threshold value Wth. Thereby, the video processing apparatus 100 appropriately determines whether or not the vehicle is stopped.

  If the fluctuation width W is greater than the threshold value Wth (step S102; Yes), the video processing apparatus 100 determines that the vehicle has not stopped and calculates the processing degree P based on the acceleration As (step S103). For example, the video processing apparatus 100 determines the processing degree P based on the absolute value of the acceleration As by referring to the map shown in FIG. Then, the video processing apparatus 100 changes the video speed magnification based on the processing degree P (step S104). For example, the video processing apparatus 100 calculates the video speed magnification from the processing degree P by referring to the map shown in FIG. Then, the video processing apparatus 100 changes the video speed of the video data Sv corresponding temporally to the processing degree P by inserting a dummy frame or the like based on the determined video speed magnification.

  On the other hand, when the fluctuation width W is equal to or smaller than the threshold value Wth (step S102; No), the video processing apparatus 100 determines that the vehicle is stopped and does not change the video speed magnification (step S105). As a result, it is possible to suppress unnecessary processing of the video data Sv while the vehicle is stopped, where no video sickness scene actually occurs.

  As described above, the video processing apparatus according to the present embodiment includes the video sickness scene detection unit and the video processing unit. The video sickness scene detecting means detects a video sickness scene in which video sickness occurs when the video data is reproduced from the video data composed of a plurality of image frames. The video processing means performs scene processing based on the degree of processing that is a detection result of the video sickness scene detection means. In this way, the video processing apparatus can appropriately convert the video data into video data that does not cause video sickness.

(Modification 1)
In the description of the first embodiment, the vehicle stop determination unit 16 determines whether or not the vehicle is stopped based on the acceleration As in the horizontal direction of the vehicle. However, the method to which the present invention is applicable is not limited to this. Instead of or in addition to this, the vehicle stop determination unit 16 may determine whether or not the vehicle is stopped based on the acceleration in the longitudinal direction of the vehicle (hereinafter referred to as “acceleration Af”).

  This will be specifically described. The vehicle stop determination unit 16 obtains the acceleration Af from the acceleration sensor 11 and calculates a fluctuation width (hereinafter referred to as “fluctuation width Wf”) of the acceleration Af within a predetermined time width. The predetermined time width described above is appropriately set based on experiments and the like. Then, the vehicle stop determination unit 16 determines whether or not the fluctuation range of the acceleration As is not limited to or in addition to the value of the acceleration As when the fluctuation range Wf is equal to or less than a predetermined threshold value (hereinafter referred to as “threshold value Wthf”). When W is less than or equal to threshold value Wth, it is determined that the vehicle is stopped. The threshold value Wthf is set to an appropriate value based on experiments or the like.

  Also by executing the above processing, the vehicle stop determination unit 16 can appropriately determine whether or not the vehicle is stopped, and unnecessarily process the video data Sv of the portion where the video sickness does not occur. Can be suppressed.

(Modification 2)
In the description of the first embodiment, the video speed conversion unit 2x converts the video speed of the temporally corresponding video data Sv according to the processing degree P calculated based on the absolute value of the acceleration As. However, the method to which the present invention is applicable is not limited to this. In addition, the video processing apparatus 100 may adjust the processing degree P based on a user input.

  A specific example of this will be described with reference to FIG. FIG. 7 shows a part of functional blocks extracted from the video processing apparatus 100 according to the second modification. As shown in FIG. 7, the video processing apparatus 100 includes an effect intensity adjustment unit 3 between the curve detection unit 17 and the video speed conversion unit 2x. The effect intensity adjustment unit 3 changes the processing degree P supplied from the curve detection unit 17 based on the user input regarding the processing degree P supplied from the input device 60 or the like, and then changes the processing degree P to the video speed conversion unit 2x. Supply the processing degree P.

  For example, when there is a user input for reducing the processing degree P, the effect intensity adjusting unit 3 decreases the processing degree P based on a predetermined formula or map. On the other hand, when there is an input to increase the processing degree P, the effect intensity adjusting unit 3 increases the processing degree P based on a predetermined formula or map. The above formula or map is appropriately created based on experiments or the like. As another example, when the user specifically specifies the rate of lowering the processing degree P, the effect strength adjusting unit 3 changes the processing degree P based on the specified ratio.

  As described above, the video processing apparatus 100 can appropriately process the video data Sv in consideration of individual differences in video sickness.

  Modification 2 can also be applied to second to fifth embodiments described later. Even in these cases, the video processing apparatus 100 includes the effect intensity adjustment unit 3 described above between the video sickness scene detection unit 1 and the video processing unit 2, and the video motion sickness scene detection unit 1 to the video processing unit 2. The processing degree P supplied to is changed based on the user input.

(Modification 3)
In the description of the first embodiment and the first modification, the vehicle stop determination unit 16 determines whether or not the vehicle is stopped based on the acceleration of the vehicle. Instead of this, or in addition to this, the vehicle stop determination unit 16 may determine whether or not the vehicle is stopped based on the traveling speed of the vehicle.

  For example, the vehicle stop determination unit 16 detects the traveling speed of the vehicle based on the vehicle speed pulse supplied from the distance sensor 13. Then, the vehicle stop determination unit 16 determines that the vehicle is stopped when the traveling speed is equal to or less than a predetermined threshold. The above-described threshold value is set to the upper limit value of the traveling speed at which the vehicle can be considered to be stopped based on, for example, experiments. As described above, the vehicle stop determination unit 16 can appropriately determine whether or not the vehicle is stopped based on the traveling speed.

[Second Embodiment]
In the first example, the video sickness scene detection unit 1 calculates the processing degree P based on the acceleration As. In the second embodiment, instead of or in addition to this, the video sickness scene detection unit 1 calculates the processing degree P based on the position information of the vehicle. Thereby, the video processing apparatus 100 appropriately sets the processing degree P and prevents the occurrence of video sickness during reproduction.

  This will be specifically described with reference to FIG. FIG. 8 is an example of the configuration of the video processing system according to the second embodiment. As shown in FIG. 8, the video processing device 100 includes a curve detection unit 17, a GPS 18, and a video speed conversion unit 2x.

  The curve detection unit 17 acquires latitude and longitude information (hereinafter referred to as “latitude / longitude information Ib”), which is the current position information of the vehicle, from the GPS 18 and calculates a curve in the travel route based on the latitude / longitude information Ib. The degree of processing P is detected and calculated according to the degree of curvature (curvature) of the curve.

  A method for calculating the above-described curve bending degree will be described with reference to FIG. FIG. 9A shows an example of fitting a part of the travel route with a circle. In FIG. 9A, points 70 a to 70 d indicate points where the curve detection unit 17 sequentially acquires the latitude / longitude information Ib by the GPS 18 while the vehicle is traveling on the route 60.

  The curve detection unit 17 derives a circle indicated by a broken line based on the latitude / longitude information Ib acquired at the points 70a to 70d, and obtains a radius (curvature radius) “R” of the circle. The radius R is calculated by, for example, an existing mathematical method for calculating the curvature radius based on the coordinates of the points 70a to 70d with FIG. 9A as the xy plane.

  Thus, the curve detection unit 17 can calculate the degree of curve of the travel route based on the predetermined number of latitude / longitude information Ib acquired immediately before. The predetermined number described above is set to an appropriate value based on experiments or the like.

  Next, a method for calculating the processing degree P will be described. The curve detection unit 17 sets the processing degree P based on the reciprocal of the radius R (that is, the curvature). Specifically, the curve detection unit 17 determines the processing degree P from the reciprocal of the radius R by referring to a predetermined formula or map. The above formula or map is created based on, for example, experiments.

  This will be described with reference to FIG. FIG. 9B is an example of a map of the reciprocal of the radius R and the processing degree P. The map shown in FIG. 9B is stored in the ROM 23 or the data storage unit 36.

  As shown in FIG. 9B, the curve detection unit 17 sets the processing degree P to be larger as the reciprocal of the radius R is larger, that is, as the curvature of the travel route is larger. Thereby, the curve detection part 17 can set the processing degree P appropriately according to a curvature with respect to the video data Sv with the high probability that the image sickness image | photographed during driving | running | working of a curve will generate | occur | produce.

  Next, returning to the description of FIG. 8 again, the processing executed by the video speed conversion unit 2x will be described. Based on the processing degree P supplied from the curve detection unit 17, the video speed conversion unit 2x refers to a predetermined map or the like as shown in FIG. The video speed is reduced by inserting a dummy frame between the Sv frames. The above-described map is created based on experiments and the like, and is stored in the ROM 23 or the data storage unit 36.

  When the processing degree P supplied from the curve detection unit 17 is supplied later than the video data Sv corresponding to the time, the video speed conversion unit 2x stores the video data Sv for a predetermined time width, for example. Processed later. The predetermined time width is set based on an experiment or the like in a time width corresponding to the above-described delay, for example. Accordingly, the video speed conversion unit 2x can process the processing degree P and the video data Sv to be processed based on the processing degree P in an appropriate manner.

(Processing flow)
Next, a processing procedure executed by the video processing apparatus 100 in the second embodiment will be described with reference to FIG. FIG. 10 is an example of a flowchart showing a processing procedure executed by the video processing apparatus 100 in the first embodiment. The video processing apparatus 100 repeatedly executes the processing of the flowchart shown in FIG. 10 according to a predetermined cycle.

  First, the video processing apparatus 100 reads latitude / longitude information Ib from the GPS 18 (step S201).

  Next, the video processing apparatus 100 calculates the radius R of the circle based on the predetermined number of latitude / longitude information acquired immediately before (step S202).

  Then, the video processing apparatus 100 sets the processing degree P based on the radius R (step S203). For example, the video processing apparatus 100 determines the processing degree P by referring to a map as illustrated in FIG. 9B based on the reciprocal of the radius R.

  Next, the video processing apparatus 100 changes the video speed magnification based on the processing degree P (step S204). Thereafter, the video processing device 100 supplies the processed video data Svr to the video recording device 300x. Thereby, the video processing apparatus 100 can suppress the occurrence of video sickness when the processed video data Svr is reproduced.

(Modification)
In the above description, the curve detection unit 17 calculates the processing degree P based on the latitude / longitude information Ib supplied from the GPS 18. Instead of this, or in addition to this, the curve detector 17 may calculate the processing degree P based on the map information regarding the travel route held in the data storage unit 36 or the like.

  For example, the curve detection unit 17 acquires the current latitude / longitude information Ib from the GPS 18 and acquires information on the radius R associated with the point corresponding to the latitude / longitude information Ib from the map information. And the curve detection part 17 calculates the process degree P by referring the map etc. as shown in FIG.9 (b) based on the said information. Thereby, the curve detection unit 17 can appropriately set the radius R while reducing the processing amount.

  In another example, the curve detection unit 17 refers to the map information based on the latitude / longitude information Ib supplied from the GPS 18 so as to grasp the detailed shape of the route that is running or is going to run. And the curve detection part 17 calculates the radius R from the path | route shape specified based on map information.

  As described above, the curve detection unit 17 can accurately calculate or acquire the radius R also from the map information.

[Third embodiment]
In the third embodiment, instead of the first embodiment and the second embodiment, the video processing unit 2 deletes a video sickness scene whose processing degree P is a certain level or more. Thereby, the video processing apparatus 100 reliably prevents the occurrence of video sickness during playback.

  This will be described with reference to FIG. FIG. 11 is a block diagram of a video processing system according to the third embodiment. As shown in FIG. 11, the video processing apparatus 100 includes a video sickness scene detection unit 1 and a video editing unit 2y.

  The video sickness scene detection unit 1 calculates the processing degree P based on the values of various sensors. For example, the video sickness scene detection unit 1 calculates the processing degree P based on the acceleration As, as in the first embodiment. In another example, the video sickness scene detection unit 1 calculates the processing degree P based on the latitude / longitude information Ib from the GPS 18 as in the second embodiment.

  The video editing unit 2y appropriately deletes temporally corresponding video data Sv based on the processing degree P supplied from the video sickness scene detection unit 1. Specifically, the video editing unit 2y compares the processing degree P with a predetermined threshold (hereinafter referred to as “threshold Pth”), and the video data Sv temporally corresponding to the processing degree P equal to or greater than the threshold Pth. delete. The threshold value Pth is set to an appropriate value based on experiments or the like. Then, the video editing unit 2y supplies the processed video data Svr to the video recording device 300x.

  In this manner, the video processing apparatus 100 can reliably suppress the occurrence of video sickness during reproduction by appropriately deleting the video data Sv that is highly likely to cause video sickness.

  The video speed conversion unit 2x supplies the processing degree P supplied from the video sickness scene detection unit 1 later than the video data Sv corresponding in time to the video sickness scene detection unit 1 as in the first and second embodiments. In this case, for example, the video data Sv is processed after being accumulated for a predetermined time width. The predetermined time width is set based on, for example, experiments on the above-described delay time width. Accordingly, the video speed conversion unit 2x can process the processing degree P and the video data Sv to be processed based on the processing degree P in an appropriate manner.

  Further, the video editing unit 2y may crossfade frames positioned before and after the video sickness scene. As a result, the video editing unit 2y can reduce visual discomfort caused by frame deletion.

(Modification 1)
In the description of the third embodiment, the video processing unit 2 includes the video editing unit 2y and deletes the video data Sv that temporally corresponds to the processing degree P that is equal to or greater than the threshold value Pth. In addition to this, the video processing unit 2 may further include a video speed conversion unit 2x.

  For example, the video processing unit 2 deletes the video data Sv temporally corresponding to the processing degree P equal to or greater than the threshold Pth, and the video speed magnification for the video data Sv temporally corresponding to the processing degree P less than the threshold Pth. Is lowered according to the processing degree P.

  As described above, the video processing unit 2 can create the post-processing video data Svr more appropriately by changing the processing method of the video data Sv according to the processing degree P.

(Modification 2)
In the description of the third embodiment, the video speed conversion unit 2x deletes the temporally corresponding video data Sv based on the processing degree P supplied from the video sickness scene detection unit 1. In addition, the video processing apparatus 100 may further adjust the processing degree P or / and the threshold value Pth based on a user input. For example, as in the second modification of the first embodiment, the video processing apparatus 100 includes an effect intensity adjustment unit between the video sickness scene detection unit 1 and the video editing unit 2y, and the processing degree P or / And the threshold value Pth is adjusted and then supplied to the video editing unit 2y. As described above, the video processing apparatus 100 can appropriately process the video data Sv in consideration of individual differences in video sickness.

[Fourth embodiment]
In the fourth embodiment, instead of the first to third embodiments, the video processing unit 2 changes the size of a video sickness scene whose processing degree P is a certain level or more. In general, when a moving image with similar movement is viewed, humans are less likely to get motion sickness when viewing a small-sized image than when viewing a large-sized image. Therefore, in the fourth embodiment, the video processing apparatus 100 prevents the occurrence of video sickness during playback by changing the size of the video sickness scene having a certain degree of processing P.

  This will be described with reference to FIG. FIG. 12 is a block diagram of a video processing system according to the fourth embodiment. As shown in FIG. 12, the video processing device 100 includes a video sickness scene detection unit 1 and a size conversion unit 2z.

  The video sickness scene detection unit 1 calculates the processing degree P based on the values of various sensors. For example, the video sickness scene detection unit 1 calculates the processing degree P based on the acceleration As, as in the first embodiment. In another example, the video sickness scene detection unit 1 calculates the processing degree P based on the latitude / longitude information Ib from the GPS 18 as in the second embodiment.

  Based on the processing degree P supplied from the video sickness scene detection unit 1, the size conversion unit 2z changes the temporally corresponding size of the video data Sv, that is, the vertical and horizontal sizes of each frame constituting the video data Sv. .

  For example, the size conversion unit 2z compares the processing degree P with a predetermined threshold (hereinafter referred to as “threshold Pth2”), and determines the size of the video data Sv corresponding temporally to the processing degree P equal to or greater than the threshold Pth2. Reduce the ratio. The above ratio is set to an appropriate value based on experiments and the like. In another example, the size conversion unit 2z increases the ratio of reducing the size as the processing degree P increases. Then, the video editing unit 2y supplies the processed video data Svr to the video recording device 300x.

  As described above, the video editing unit 2y can appropriately generate post-processed video data Svr that does not cause video sickness.

(Modification 1)
In the description of the fourth embodiment, the video processing unit 2 includes the size conversion unit 2z and reduces the size of the video data Sv based on the processing degree P. In addition to this, the video processing unit 2 may further include a video speed conversion unit 2x and / or a video editing unit 2y. In this case, the video processing unit 2 changes the processing method of the video data Sv according to the value of the processing degree P, for example.

  A specific example of this will be described. The video processing unit 2 changes the video speed of the video data Sv that temporally corresponds to the processing degree P less than the threshold Pth2 based on the processing degree P, and temporally corresponds to the processing degree P that is greater than or equal to the threshold Pth2 and less than the threshold Pth. The video data Sv is reduced, and the video data Sv temporally corresponding to the processing degree P equal to or greater than the threshold Pth is deleted. In this example, the threshold value Pth is set to a value larger than the threshold value Pth2.

  As described above, the video processing unit 2 can create the post-processing video data Svr more appropriately by changing the processing method of the video data Sv according to the processing degree P.

(Modification 2)
In the description of the fourth embodiment, the video speed conversion unit 2x reduces the size of the video data Sv that temporally corresponds to the processing degree P based on the processing degree P supplied from the video sickness scene detection unit 1. In addition, the video processing apparatus 100 may further adjust the processing degree P or / and the threshold value Pth2 based on a user input. For example, as in Modification 2 of the third embodiment, the video processing device 100 includes an effect intensity adjustment unit between the video sickness scene detection unit 1 and the video editing unit 2y, and the processing degree P or / And the threshold value Pth2 is adjusted. As described above, the video processing apparatus 100 can appropriately process the video data Sv in consideration of individual differences in video sickness.

[Fifth embodiment]
In the first to fourth embodiments, the video processing device 100 processes the video data Sv captured by the imaging device 200x before recording it in the video recording device 300x. However, the method to which the present invention is applicable is not limited to this. Instead of this, the video processing apparatus 100 may process the video data Sv already recorded at the time of reproduction.

  This will be described with reference to FIG. FIG. 13 shows a configuration of a video processing system according to the fifth embodiment. As shown in FIG. 13, the video processing system includes a recording device 200y, a video processing device 100, and a display device 300y.

  The recording device 200y holds the video data Sv generated by the imaging device mounted on the vehicle, and holds values of various sensors (sensor values Se) detected when the video data Sv is generated in association with the video data Sv. . The sensor value Se described above corresponds to, for example, detection values (acceleration As, Af) of the acceleration sensor 11 or latitude / longitude information Ib supplied from the GPS 18.

  The video sickness scene detection unit 1 acquires the sensor value Se from the recording device 200y, and calculates the processing degree P. For example, when the sensor value Se is the acceleration As, the video sickness scene detection unit 1 calculates the processing degree P based on the map of FIG. In another example, when the sensor value Se is latitude / longitude information Ib, the video sickness scene detection unit 1 calculates the radius R based on the sensor value Se and determines the processing degree P based on the map of FIG. 9B.

  The video processing unit 2 acquires the video data Sv from the recording device 200y and processes the video data Sv based on the processing degree P supplied from the video sickness scene detection unit 1. For example, the video processing unit 2 changes the video speed magnification of the temporally corresponding video data Sv based on the processing degree P as described above. In another example, the video processing unit 2 deletes temporally corresponding video data Sv based on the processing degree P. In yet another example, the video processing unit 2 changes the size of the video data Sv based on the processing degree P. Then, the video processing unit 2 supplies the processed video data Svr to the display device 300y.

  The display device 300y displays the processed video data Svr supplied from the video processing unit 2.

  In this way, the video processing device 100 can prevent the occurrence of video sickness by processing the video data Sv from the recording device 200y based on the sensor value Se and outputting it to the display device 300y during reproduction.

(Modification 1)
In the fifth embodiment, the video processing device 100 processes the video data Sv based on the sensor value Se supplied from the recording device 200y. However, the configuration to which the present invention is applicable is not limited to this. For example, instead of this, or in addition to this, the video processing apparatus 100, as described in [Summary Description], parameters obtained by performing image processing on each frame constituting the video data Sv, and the like. The video data Sv may be processed based on information obtained by performing image processing on the video data Sv. In this case, for example, the video processing apparatus 100 sets the processing degree P based on the above-described parameters and other information based on a predetermined map or expression, and processes the video data Sv based on the processing degree P. The above-described map and the like are appropriately set based on experiments and the like. As described above, according to the first modification, the video processing apparatus 100 can appropriately process the video data Sv based only on the video data Sv without using the sensor value Se.

(Modification 2)
In the fifth embodiment, the video processing device 100 acquires the video data Sv and the sensor value Se from the recording device 200y, and reproduces the processed video data Svr by the display device 300y. However, the configuration to which the present invention is applicable is not limited to this. Instead, the video processing device 100 acquires the video data Sv and the sensor value Se from the recording device 200y to generate the processed video data Svr when the playback is not in progress, and generates the processed video data Svr as the recording device 200y. Or you may record to another video recording device. Even with such a configuration, the present invention can be suitably applied.

(Modification 3)
In the fifth embodiment, the video processing device 100 acquires the video data Sv and the sensor value Se from the recording device 200y during reproduction. Instead, the video processing device 100 may acquire the video data Sv and the processing degree P from the recording device 200y. That is, in this case, the processing degree P is calculated based on the sensor value Se in advance before recording in the recording apparatus 200y. This also makes it possible to suitably apply the present invention.

[Application field]
The present invention can be applied to various devices that perform video processing. For example, it is widely applied to various devices such as a navigation device, a drive recorder, and a camera mounted on a bicycle. Therefore, the configuration of FIG. 2 described above is an example, and the configuration to which the present invention can be applied is not necessarily limited thereto. For example, as shown in the fifth embodiment, the video processing device 100 may receive the sensor value Se from another device.

DESCRIPTION OF SYMBOLS 1 Image sickness scene detection part 2 Image processing part 11 Acceleration sensor 18 GPS
22 CPU
100 video processing device 200 video input device 300 video output device

According to the first aspect of the present invention, the video processing apparatus acquires a video from a camera mounted on a moving body, and whether or not the moving body is located at a place where the moving path is curved. A curve determining step for determining, an image processing step for processing the image determined to have been acquired at the curved position, and detecting whether or not the moving body is stopped A stop detection step, and a control step of controlling the image processing means so as not to perform the processing on the image acquired at a position where the moving body is stopped .

According to a fifth aspect of the present invention, in the video processing method, an image acquisition step of acquiring an image from a camera mounted on a moving body, and whether or not the moving body is located at a place where the moving path curves. A curve determining step for determining, an image processing step for processing the image determined to have been acquired at the curved position, and detecting whether or not the moving body is stopped A stop detection step, and a control step of controlling the image processing step so as not to perform the processing on the image acquired at a position where the moving body is stopped.

The invention according to claim 6 is an image processing program executed by a computer, image acquisition means for acquiring an image from a camera mounted on a moving body, and a position where the moving body curves in the moving path. Curve determining means for determining whether or not the image is located; image processing means for processing the image determined to have been acquired by the curve determining means at the curved position; and whether or not the moving body is stopped A stop detection means for detecting whether or not the video acquired at a position where the moving body is stopped causes the computer to function as a control means for controlling the video processing means so as not to perform the processing. .

Claims (16)

Video sickness scene detection means for detecting a scene in which video sickness occurs during reproduction of the video data from video data composed of a plurality of image frames;
Video processing means for processing the scene based on the detection result of the video sickness scene detection means;
A video processing apparatus comprising:   The video sickness scene detection means determines that the probability of video sickness is high and the degree of video sickness is high as the video change during reproduction of the video data is large. Video processing equipment. The video data is taken from an imaging device mounted on a moving body,
3. The video processing apparatus according to claim 1, wherein the video sickness scene detection unit detects the scene based on information on the behavior of the moving object temporally corresponding to the video data.   The video processing apparatus according to claim 3, wherein the video sickness scene detecting unit detects the scene based on an acceleration in a side surface direction of the moving body.   5. The video processing apparatus according to claim 3, wherein the video sickness scene detection unit determines that video sickness does not occur in video data corresponding in time to the stop of the moving body.   6. The video processing apparatus according to claim 5, wherein the video sickness scene detection means determines whether or not the moving body is at a stop time based on the speed of the moving body and / or the acceleration of the moving body. .   The video processing apparatus according to claim 3, wherein the video sickness scene detection unit detects the scene based on a curvature of a travel route of the moving body.   The video processing apparatus according to claim 3, wherein the video sickness scene detection unit detects the scene based on an acceleration in a traveling direction of the moving body.   The video processing apparatus according to claim 3, wherein the video sickness scene detection unit detects the scene based on an inclination in a traveling direction of a travel route of the moving body. The video sickness scene detecting means calculates a processing degree indicating a degree to be processed by the video processing means,
The video according to any one of claims 1 to 9, wherein the video processing means sets a lower playback speed of video data corresponding to the processing degree in time as the processing degree is larger. Processing equipment. The video sickness scene detecting means calculates a processing degree indicating a degree to be processed by the video processing means,
The said image processing means reduces the display size of the video data temporally corresponding to the said processing degree when the said processing degree is more than a 1st threshold value. The video processing apparatus described. The video sickness scene detecting means calculates a processing degree indicating a degree to be processed by the video processing means,
12. The video processing unit according to claim 1, wherein when the processing level is equal to or greater than a second threshold, the video processing unit deletes a frame constituting video data that temporally corresponds to the processing level. The video processing apparatus described in 1. Mounted on the moving body,
The video sickness scene detection means calculates the curvature based on the newest predetermined number of position information acquired from the positioning system,
The video processing means holds video data temporally corresponding to position information used for calculating the curvature until the calculation of the curvature, and processes the video data based on the calculated curvature. Item 13. The video processing device according to any one of Items 9 to 12. A video sickness scene detection step of detecting a scene in which video sickness occurs during playback of the video data from video data composed of a plurality of image frames;
A video processing step for processing the scene based on the detection result of the video sickness scene detecting means,
A video processing method comprising: A video processing program executed by a computer,
Video sickness scene detection means for detecting a scene in which video sickness occurs during reproduction of the video data from video data composed of a plurality of image frames;
Video processing means for processing the scene based on the detection result of the video sickness scene detection means;
A video processing program comprising:   A storage medium storing the program according to claim 15.

Images