WO2019124633A1 - Procédé orienté syntaxe de détection d'objet d'escalade de mur dans une vidéo comprimée - Google Patents

Procédé orienté syntaxe de détection d'objet d'escalade de mur dans une vidéo comprimée Download PDF

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Publication number
WO2019124633A1
WO2019124633A1 PCT/KR2018/002555 KR2018002555W WO2019124633A1 WO 2019124633 A1 WO2019124633 A1 WO 2019124633A1 KR 2018002555 W KR2018002555 W KR 2018002555W WO 2019124633 A1 WO2019124633 A1 WO 2019124633A1
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moving object
image
compressed image
region
motion vector
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PCT/KR2018/002555
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English (en)
Korean (ko)
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이성진
정승훈
배현성
이현우
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이노뎁 주식회사
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/136—Incoming video signal characteristics or properties
    • H04N19/137—Motion inside a coding unit, e.g. average field, frame or block difference
    • H04N19/139—Analysis of motion vectors, e.g. their magnitude, direction, variance or reliability
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/65—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using error resilience
    • H04N19/67—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using error resilience involving unequal error protection [UEP], i.e. providing protection according to the importance of the data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards

Definitions

  • the present invention relates generally to techniques for effectively identifying object wartime from compressed images such as H.264 AVC and H.265 HEVC.
  • the present invention relates to a method and an apparatus for detecting a moving image of a compressed image generated by a CCTV camera, that is, an area in which there is a significant motion, Based on a syntax such as a motion vector and a coding type, and observing the movement of the moving object region, thereby detecting an object witnessing event when the object passes through a walktaming boundary zone.
  • the image sensing system adopts compressed image for efficiency of storage space.
  • complicated image compression techniques of high compression ratio such as H.264 AVC and H.265 HEVC are adopted.
  • a compressed image is generated according to one of these technical specifications, and the apparatus for reproducing the moving image receives the compressed image, and if the compressed image is received, As shown in FIG.
  • a process of decoding a compressed image to obtain a reproduced image, that is, an original image in which a decompressed image has been obtained, is then processed.
  • a moving picture decoding apparatus includes a syntax analyzer 11, an entropy decoder 12, an inverse transformer 13, a motion vector calculator 14, a predictor 15, a deblocking filter 16).
  • Such hardware modules process compressed images sequentially, decompress them, and restore the original image data.
  • the parser 11 parses the motion vector and the coding type for the coding unit of the compressed image.
  • Such a coding unit is generally an image block such as a macroblock or a sub-block, but may be implemented not exactly in accordance with a technical standard.
  • FIG. 2 is a flowchart illustrating a process of detecting object witness from a compressed image in a conventional image analysis solution.
  • a compressed image is decoded according to H.264 AVC and H.265 HEVC (S10), and the frame images of the reproduced image are downscaled to a small image, for example, 320x240 (S20).
  • S10 H.264 AVC and H.265 HEVC
  • S20 320x240
  • downscaling is performed to reduce the processing burden in the subsequent process.
  • differential images are obtained for the resized frame images, and the moving object is extracted through the image analysis (S30).
  • the moving path of the extracted moving objects is acquired through image analysis, and it is judged that someone is walks in the case of passing through the preset wardhound boundary zone (S40).
  • an object of the present invention to provide an image processing apparatus and a method for processing a moving image in a region where there is a significant motion for a compressed image generated by, for example, a CCTV camera
  • the present invention provides a technique for extracting an object based on a syntax such as a motion vector and a coding type, and observing a motion of the moving object region to detect an object witnessing event when the object passes through a walktake boundary zone.
  • a method for detecting a subject-based moonshade based on a compressed image comprising: a first step of obtaining a motion vector and a coding type for a coding unit by parsing a bitstream of the compressed image; A second step of acquiring a motion vector accumulation value for a predetermined time for each of a plurality of image blocks constituting a compressed image; A third step of comparing the accumulated value of the motion vector with a preset first threshold value for a plurality of image blocks; A fourth step of marking an image block having a motion vector accumulation value exceeding a first threshold value as a moving object region; And a fifth step of monitoring the movement of the moving object area and generating an object walding event for the moving object area when the moving object area passes through a preset warding boundary area of the compressed image.
  • an image block constituting a compressed image may include a macro block and a sub-block.
  • the center coordinates of the moving object region are calculated for a series of image frames constituting the compressed image.
  • the fifth step when the moving object area is in the ID unassigned state, a step of newly issuing and allocating the Unique ID is performed. And revoking the allocated Unique ID if the moving object region disappears in the series of image frames.
  • a method for detecting object lag time comprising the steps of: a) identifying a plurality of adjacent image blocks (hereinafter, referred to as 'neighboring blocks') around a moving object region; Comparing a motion vector value with a predetermined second threshold value for a plurality of neighboring blocks; Further comprising: marking a neighboring block having a motion vector value exceeding a second threshold as a moving object region; D) marking a neighboring block having a coding type of an intra picture among a plurality of neighboring blocks as a moving object region; Marking a predetermined number or less of unmarked image blocks surrounded by the moving object area as a moving object area by performing interpolation on the plurality of moving object areas.
  • a computer-readable nonvolatile recording medium records a program for causing a computer to execute a method of detecting a syntax-based object stuttering for a compressed image as described above.
  • the moving object region is extracted from the CCTV image without performing the complicated processing such as decoding, downscaling resizing, differential image acquisition, and image analysis on the CCTV compressed image, There is an advantage that performance improvement can be obtained.
  • the present invention it is possible to identify in real time that a person walks from a CCTV photographed image without performing complex processing such as decoding, downscaling, differential image acquisition, and image analysis on a compressed image, There is an advantage that the prevention effect can be enhanced.
  • FIG. 1 is a block diagram showing a general configuration of a moving picture decoding apparatus
  • FIG. 2 is a flowchart showing a process of detecting an object wallyhoot from a compressed image in the prior art
  • FIG. 3 is a flowchart showing an overall process for detecting object wartime from a compressed image according to the present invention
  • FIG. 4 is a flowchart showing an embodiment of a process of detecting valid motion from a compressed image in the present invention.
  • FIG. 5 is a diagram illustrating an example of a result of applying a valid motion region detection process according to the present invention to a CCTV monitoring screen.
  • Figures 6 and 7 are partially enlarged views of the main part of Figure 5;
  • FIG. 8 is a flowchart illustrating an example of a process of detecting a boundary region for a moving object region in the present invention.
  • FIG. 9 is a view showing an example of a result of applying a boundary region detection process according to the present invention to a compressed image.
  • Figs. 10 and 11 are partially enlarged views of the main part of Fig. 9; Fig.
  • FIG. 12 is a diagram illustrating an example of a result of summarizing a moving object region through interpolation in the present invention.
  • Figs. 13 and 14 are partially enlarged views of the main part of Fig. 12; Fig.
  • 15 is a flowchart showing an embodiment of a process of detecting an object wedge event on the basis of a movement trajectory of a moving object area in the present invention.
  • 16 is a diagram illustrating an example in which a unique ID is assigned to a moving object area in the present invention.
  • 17 is a diagram showing an example in which center coordinates are set in a moving object area in the present invention.
  • FIG. 3 is a flow chart illustrating the overall process of detecting object fence-climbing from a compressed image in accordance with the present invention.
  • the object detection process according to the present invention can perform well in a system for handling a series of compressed images, for example, an image analysis server in a CCTV image control system.
  • a bitstream of a compressed image is parsed without decoding a compressed image, and syntax information such as a macroblock and a sub-block, preferably a motion vector, And the coding type (Coding Type) information.
  • the obtained moving object area does not accurately reflect the boundary line of the moving object as shown in the image attached to this specification, but has a high processing speed and high reliability. Then, in the present invention, based on the obtained moving object area, it is discriminated whether or not there is an object wall cast in the compressed image, that is, whether the person walks.
  • the present invention it is possible to extract a moving object region without decoding a compressed image and to detect object walks.
  • the apparatus or software to which the present invention is applied should not perform the operation of decoding the compressed image, and the scope of the present invention is not limited thereto.
  • Step S100 First, an effective motion that is substantially meaningful from the compressed image is detected based on the motion vector of the compressed image, and the image area in which the valid motion is detected is set as the moving object area.
  • the motion vector and coding type of the coding unit of the compressed image are parsed according to a moving picture compression standard such as H.264 AVC and H.265 HEVC.
  • the size of the coding unit is generally 64 x 64 pixels to 4 x 4 pixels and can be set to be flexible.
  • a predetermined time period e.g., 500 msec
  • Step S200 Next, the boundary region is detected based on the motion vector and the coding type for the moving object region detected in the previous step (S100). For this purpose, when a plurality of image blocks neighboring the image block marked as the moving object region are examined and the motion vector is generated over a second threshold value (for example, 0) or the coding type is an intra picture, Mark the block as a moving object area. In this process, the image block is substantially a block of the moving object area detected in step S100.
  • a second threshold value for example, 0
  • the coding type is an intra picture
  • the image block If an effective motion is found and the image block has some motion in the vicinity of the moving object area, it is marked as a moving object area because it is likely to be a lump with the previous moving object area.
  • the intra picture adjacent to the image block already detected as the moving object region is estimated as a lump together with the previously extracted moving object region.
  • Step S300 Interpolation is applied to the moving object area detected in the previous steps S100 and S200 to arrange the fragmentation of the moving object area.
  • the moving object region is determined in units of image blocks, in reality, there is an image block which is not marked as the moving object region in the middle even though it is one moving object (for example, As shown in FIG.
  • Step S400 The moving object region is quickly extracted based on the syntax (motion vector, coding type) of the coding unit for the compressed image through the above process.
  • step S400 if someone is wrestling in the compressed image by using the extracted result of the moving object area, it is detected to prevent crime. In the present specification, this is referred to as an " object waltz. &Quot; The purpose of this study is to improve the effectiveness of crime prevention by letting the control personnel know more about the fact that the video object system detects the current object video and the video point where the object video is detected. Also, in the aspect of ensuring the after - evidence,
  • the movement of the moving object area is monitored, and when the moving object crosses the preset warding boundary area in the compressed image, an object walding event is generated for the moving object area.
  • FIG. 4 is a flowchart illustrating an embodiment of a process for detecting valid motion from a compressed image in the present invention
  • FIG. 5 is a view illustrating an example of a result of applying the effective moving area detection process according to the present invention to a CCTV monitoring screen.
  • Step S110 First, the coding unit of the compressed image is parsed to obtain a motion vector and a coding type.
  • the moving picture decoding apparatus performs a syntax analysis (header parsing) and a motion vector operation on a stream of a compressed image according to a moving picture compression standard such as H.264 AVC and H.265 HEVC.
  • a moving picture compression standard such as H.264 AVC and H.265 HEVC.
  • Step S120 The motion vector accumulation value for a preset time (for example, 500 ms) is obtained for each of the plurality of image blocks constituting the compressed image.
  • This step is presented with the intent to detect any valid motion that is substantially meaningful from the compressed image, such as a running car, a runner, or a crowd fighting with each other.
  • the shaking leaves, the ghost appearing for a while, and the shadows that change slightly due to the reflection of light are prevented from being detected because they are moving objects, but they are meaningless objects.
  • the motion vector accumulation value is obtained by accumulating the motion vectors in units of one or more image blocks for a preset predetermined time (for example, 500 msec).
  • the image block is used as a concept including a macro block and a sub-block.
  • Steps S130 and S140 The motion vector accumulation value is compared with a preset first threshold value (e.g., 20) for a plurality of image blocks, and an image block having a motion vector accumulation value exceeding the first threshold value, Lt; / RTI >
  • a preset first threshold value e.g. 20
  • a significant motion that is, a valid motion is detected in the corresponding image block, and is marked as a moving object region.
  • the degree of movement is such that the control personnel are worthy of interest.
  • the cumulative value for a predetermined time period is small enough to not exceed the first threshold value even if a motion vector occurs, the change in the image is estimated to be insignificant and insignificant, and ignored in the detection step.
  • Step S150 The moving object region is displayed on the reproduction screen of the compressed image so as to be distinguished from the general image.
  • FIG. 5 is a diagram illustrating an example of a result of applying a valid motion region detection process to a CCTV monitoring screen.
  • a plurality of image blocks indicating a cumulative motion vector value exceeding a first threshold value are marked as a moving object region, Line box.
  • Figs. 6 and 7 are enlarged views of main parts in Fig. 5.
  • Fig. 5 is a diagram illustrating an example of a result of applying a valid motion region detection process to a CCTV monitoring screen.
  • a plurality of image blocks indicating a cumulative motion vector value exceeding a first threshold value are marked as a moving object region, Line box.
  • Figs. 6 and 7 are enlarged views of main parts in Fig. 5.
  • the sidewalk block, the road, and the shadowed portion are not displayed as the moving object area, while the walking people and the traveling car are displayed as the moving object area.
  • the moving object region is represented by a thick line block, but it is more preferable that the CCTV monitor screen expresses the moving object region in a color that the controller can identify immediately.
  • FIG. 8 is a flowchart illustrating an embodiment of a process of detecting a boundary region for a moving object region in the present invention.
  • the moving object is not properly marked and only a part of the moving object is marked.
  • you look at a person walking or a car in motion you can find that not all of the objects are marked, but only some of the blocks are marked.
  • a plurality of moving object areas are marked for one moving object. This means that the judgment criterion of the moving object region adopted in the previous (S100) is very useful for filtering out the general region, but it is very strict.
  • Step S210 First, a plurality of adjacent image blocks are identified centering on the image block marked as the moving object region by the previous step (S100). These are referred to herein as " neighboring blocks ". These neighboring blocks are portions that are not marked as a moving object region according to S100. In the process of FIG. 8, a more detailed look at the neighboring blocks will be made to see if there are any neighboring blocks that can be included in the boundary of the moving object region.
  • Step S220 S230: The motion vector value is compared with a preset second threshold value (e.g., 0) for a plurality of neighboring blocks, and a neighboring block having a motion vector value exceeding the second threshold value is marked as a moving object region do. If there is a motion that is located adjacent to the recognized moving object region, which is substantially effective, the moving image block is likely to be a lump of the moving object region ahead of the moving object region. Therefore, this neighboring block is also marked as a moving object area.
  • a preset second threshold value e.g., 0
  • Step S240 Also, among the plurality of neighboring blocks, marking that the coding type is intra picture is marked as the moving object area.
  • marking that the coding type is intra picture is marked as the moving object area.
  • the intra picture adjacent to the image block already detected as the moving object region is safer to maintain the setting of the extracted moving object region.
  • Step S250 The moving object region is displayed on the reproduction screen of the compressed image so as to be distinguished from the general image.
  • FIG. 9 is a diagram showing an example of a result applied to the boundary region detection process according to the present invention.
  • a plurality of image blocks marked as a moving object region are displayed as thick line boxes on a monitor screen.
  • the moving object area is further expanded in FIGS. 10 and 11 to cover the entire moving object Can be found.
  • FIG. 12 is a diagram illustrating an example of a result of summarizing a moving object region through interpolation in the present invention
  • FIGS. 13 and 14 are enlarged views of main parts in FIG.
  • Step S300 is a process of organizing the division of the moving object region by applying interpolation to the moving object region detected in the previous steps S100 and S200.
  • a non-marking image block is found between moving object areas indicated by blocks. If there are non-marking image blocks in the middle, it is difficult to judge whether they are objects to be considered as individual moving objects or as a mass. In particular, since it is displayed mottled on the monitor screen of the CCTV video control system, it is difficult for the control personnel to grasp it immediately. Furthermore, if the moving object area is fragmented, the result of step S400 may become inaccurate, and in particular, the process of step S400 becomes complicated because the number of moving object areas becomes large.
  • the present invention if one or a small number of non-marking image blocks surrounded by a plurality of image blocks marked as a moving object region exist, they are marked as a moving object region, which is called interpolation. 9 and 12, all non-marking image blocks existing between the moving object areas are marked as moving object areas. This makes it possible to derive a more intuitive and accurate moving object detection result for reference by the control personnel.
  • FIG. 15 is a flowchart illustrating an embodiment of a process for detecting an object witnessing event based on a movement trajectory of a moving object region in the present invention.
  • the present invention extracts a moving object region based on syntax information that can be directly obtained from a coding unit of a compressed image. It is not necessary to decode a compressed image of the conventional technique to acquire and analyze a difference image with respect to the original image, thereby achieving a processing speed improvement of up to 20 times according to the inventor's test. However, this approach has the drawback of being less accurate. There is a conceptual difference in that it does not extract the moving object itself but extracts a block of the image block which is assumed to contain the moving object.
  • the present invention adopts a different approach from the prior art in the process of determining whether a person walks on a CCTV shot image.
  • the center coordinates of a block of image blocks estimated to contain the moving object, that is, a moving object region, over a series of image frames are calculated and the moving locus thereof is monitored.
  • An object wandering event is generated for the moving object area when the movement locus of the center coordinate passes through the warding boundary area.
  • Step S410 First, if a moving object region that is not assigned an ID is found to handle the moving object region as one object, an Unique ID is newly issued and assigned. That is, in the previous process, the chunks of connected image blocks marked as moving object area are treated as one object (object). In order to implement this in the software processing process, a unique ID is assigned to a moving object area (a block of image blocks) and managed.
  • FIG. 16 shows an example in which a unique ID is assigned to a moving object area.
  • step S410 it is necessary to determine whether or not the blocks of the image blocks marked as the moving object region are the same between the series of image frames. This is because it is possible to judge whether or not the Unique ID has been previously assigned to the moving object area being handled.
  • the present invention does not deal with the contents of the original video image but checks whether or not the video block is the moving object area, so that it is impossible to precisely check whether or not the mass of the moving object area in the preceding and subsequent video frames is identical. That is, since the contents of the image included in the image are not grasped, the change can not be identified, for example, when the cat is replaced by a dog between the front and back frames at the same point. However, it is very unlikely that the time interval between frames is very short and that the observation object of the video control system moves at normal speed.
  • Steps S420, S430, and S440 Next, the movement of the moving object area is monitored to see if it passes through the warding boundary area.
  • the center coordinates (cx, cy) are calculated for each moving object region in a series of image frames constituting the compressed image. At this time, the frame in which the moving object area is not found can be ignored, and it is preferable to calculate the center coordinates based on the above Unique ID to manage the identity of the moving object area.
  • a rectangle optimally including a moving object area may be formed as a virtual center, and then the center coordinates of the rectangle may be set as the center coordinates (cx, cy) of the moving object area.
  • the trajectory of the center coordinates is monitored over a series of video frames over time, and it is estimated that somebody walks when the movement trajectory of the center coordinates passes through the preset walks boundary region for the compressed image And generates an object woofer event for the moving object area.
  • a region of interest In the case of CCTV video surveillance, it is not necessary to monitor whether or not someone walks in all areas of the area, but it is common to select some areas where crime is likely to occur. This region is referred to as a 'region of interest (ROI)'.
  • ROI region of interest
  • a boundary line in which a geographical feature can occur, is set as a region of interest. Depending on the purpose of the control, these areas of interest are preset in the video control system.
  • Step S450 The moving object area where the object walding event occurs is displayed on the reproduction screen of the compressed image so as to be distinguished from the general image.
  • the controller of the video control system can immediately recognize the image point where the object moonshots are detected, thereby observing with higher attentiveness. This can be equally helpful in the process of securing evidence.
  • the present invention can be embodied in the form of computer readable code on a computer-readable non-volatile recording medium.
  • a non-volatile recording medium includes all kinds of storage devices for storing computer-readable data such as a hard disk, an SSD, a CD-ROM, a NAS, a magnetic tape, a web disk, a cloud disk, And the code may be distributed and stored in the storage device of the computer.

Abstract

La présente invention concerne une technologie qui extrait d'une vidéo comprimée, générée par une caméra de CCTV par exemple, une région ayant un mouvement significatif, c'est-à-dire une région d'objet en mouvement, dans des unités de bloc d'image de la vidéo comprimée sur la base d'une syntaxe, telle que des vecteurs de mouvement et des types de codage, sans avoir recours à un traitement d'image complexe comme dans la technologie classique, et qui observe le mouvement dans la région d'objet en mouvement pour détecter un événement d'objet d'escalade de mur dans le cas d'une pénétration dans une région de délimitation d'escalade de mur. Selon la présente invention, un objet escaladant un mur dans une vidéo filmée par CCTV peut être distingué en temps réel sans avoir à recourir à un traitement complexe tel qu'un décodage, un redimensionnement à l'échelle inférieure, une acquisition d'image différentielle, une analyse d'image, et analogue, d'une vidéo comprimée, ce qui permet d'améliorer l'effet anti-crime d'un système de vidéosurveillance.
PCT/KR2018/002555 2017-12-20 2018-03-04 Procédé orienté syntaxe de détection d'objet d'escalade de mur dans une vidéo comprimée WO2019124633A1 (fr)

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CN113066248B (zh) * 2021-03-25 2021-11-05 福建省凯特科技有限公司 基于视频图像处理的智慧社区建设安防监控智能管理系统

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