WO2020027512A1

WO2020027512A1 - Method for syntax-based object tracking control for compressed image by ptz camera

Info

Publication number: WO2020027512A1
Application number: PCT/KR2019/009373
Authority: WO
Inventors: 이현우; 정승훈; 이성진
Original assignee: 이노뎁 주식회사
Priority date: 2018-07-30
Filing date: 2019-07-29
Publication date: 2020-02-06
Also published as: KR20200013335A; KR102080456B1

Abstract

The present invention generally relates to a technique for effectively tracking a moving object by using a PTZ camera in a CCTV control system. More specifically, unlike the conventional technique for a compressed image in which an object is identified through a complicated image processing to enable tracking control of a PTZ camera, the present invention relates to a technique in which a syntax (e.g., a motion vector and a coding type) obtained by parsing compressed image data is used to extract an area in which significant motion exists in an image, that is, a moving object area, and then make the moving object area be followed, so as to enable controlling of object tracking of a PTZ camera with a small amount of calculation. According to the present invention, it is possible to control object tracking of a PTZ camera even with a calculation amount corresponding to about 1/20 of that of the conventional technique, so that it is advantageous that the number of PTZ camera reception channels of a CCTV control system can be significantly increased even without large investment.

Description

Object Tracking Control Method of Syntax-based PTZ Camera for Compressed Images

The present invention generally relates to a technique for effectively tracking a moving object using a PTZ camera in a CCTV control system.

More specifically, the present invention is a syntax (eg, motion vector, coding) obtained by parsing compressed image data rather than tracking and controlling an PTZ camera by identifying an object through complex image processing as in the prior art. It is related to a technology that can control the object tracking of a PTZ camera by extracting a region in which something meaningful movement exists in the image, that is, a moving object region and following the moving object region by using a small number of operations.

Recently, it is common to establish a video control system using CCTV for crime prevention, illegal surveillance, and securing after evidence. With multiple CCTV cameras installed by region, images generated by these CCTV cameras are displayed on a monitor and stored in a storage device. When a control agent finds a scene where a crime or accident occurs, he or she immediately responds appropriately and, if necessary, retrieves the video stored in the storage to secure post evidence.

PTZ cameras are often used to enhance the control effect in such CCTV control systems. Pan-Tilt-Zoom (PTZ) cameras are cameras whose supports can rotate up, down, left and right and adjust the zoom ratio of the lens. The PTZ camera may move the surveillance area by a panning operation rotated 360 degrees in the horizontal direction and a tilting operation rotated at an angle in the vertical direction, and enlarge or take a photograph of the subject by changing the zoom ratio of the lens.

In this way, PTZ cameras have been used actively in the field of video control because they can be shot while changing targets or by tracking specific targets. Also, it can be used by combining general camera and PTZ camera. In this case, a general camera can be used to capture and observe a panoramic image over a relatively large area, while a PTZ camera performs object tracking and monitoring for a specific target. The object tracking operation of the PTZ camera can be controlled manually by the controller, but can also be controlled automatically.

However, automatically controlling object tracking of PTZ cameras requires a considerable amount of computational power. Recently, high-compression complex video compression technologies such as H.264 AVC and H.265 HEVC have been adopted for CCTV cameras. When the camera provides a compressed image by capturing the surroundings, the CCTV control system must decode the compressed image in reverse according to the technical specifications and perform image processing analysis on the originally photographed image thus obtained.

Tracking control of a specific object on a PTZ camera requires analyzing the original image to identify the moving object and identifying the moving object in a series of image frames. This is because panning, tilting, and zooming the PTZ camera require knowing how the object is moving. Significant computation is required to identify moving objects and detect motion from compressed images such as H.264 AVC and H.265 HEVC generated by PTZ cameras or other CCTV cameras around them.

First, FIG. 1 is a block diagram illustrating a general configuration of a video decoding apparatus according to the H.264 AVC Technical Standard. Referring to FIG. 1, a video decoding apparatus according to H.264 AVC includes a parser 11, an entropy decoder 12, an inverse converter 13, a motion vector operator 14, a predictor 15, and a deblocking filter ( 16) is configured to include. These hardware modules process compressed video sequentially to decompress and restore the original video data. At this time, 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 subblock.

2 is a flowchart illustrating an object tracking control process of a PTZ camera in a conventional video analysis solution.

Referring to FIG. 2, in the prior art, the compressed image is decoded according to H.264 AVC and H.265 HEVC, etc. (S10), and the frame images of the reproduced image are downscaled to a small image, for example, 320 × 240 (S20). At this time, the reason for downscaling resizing is to reduce the processing burden in the subsequent process. Then, after obtaining differential images of the resized frame images, moving objects are extracted through image analysis and coordinates of the moving objects are calculated (S30). Then, by panning, tilting, and zooming the PTZ camera using the size and coordinates of the moving object, the moving object is tracked and photographed (S40).

In the prior art, to extract a moving object, compressed image decoding, downscale resizing, and image analysis are performed. These are very complicated processes, and therefore, in a conventional video control system, the capacity that a single video analysis server can process simultaneously is quite limited. Accordingly, the video channel of a PTZ camera that can be accommodated by a high performance video analysis server is usually only a maximum of 16 channels, which has a considerable difficulty in increasing the number of PTZ cameras.

An object of the present invention is to provide a technique for effectively tracking a moving object using a PTZ camera in general CCTV control system.

In particular, it is an object of the present invention to utilize a syntax (eg, motion vector, coding type) obtained by parsing compressed image data rather than tracking a PTZ camera by identifying an object through a complex image processing for a compressed image as in the prior art. By extracting an area where there is something significant movement in the image, that is, a moving object area and following the moving object area, it is possible to provide a technique for controlling object tracking of a PTZ camera with a small number of operations.

In order to achieve the above object, an object tracking control method of a syntax-based PTZ camera for a compressed image according to the present invention includes 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 obtaining a motion vector cumulative value for a first preset time for each of the plurality of image blocks constituting the compressed image; A third step of comparing a motion vector cumulative value with a 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 as a moving object region; A fifth step of identifying a tracked moving object area to be tracked by the PTZ camera among the at least one marked moving object area; A sixth step of acquiring position information and size information of the tracked moving object region from the current frame image; A seventh step of performing panning and tilting control on the PTZ camera based on the positional information of the area of the tracking target object; And an eighth step of performing zoom control on the PTZ camera using the size information of the area of the tracking target object.

At this time, the object tracking control method of the PTZ camera according to the present invention, calculating a global motion vector corresponding to the average value of the motion vector for each frame; And subtracting the global motion vector calculated for the frame with respect to the motion vector. In this case, the global motion vector may be calculated by summing all the motion vectors acquired in the frame and dividing by the total number of image blocks belonging to the frame.

In addition, the object tracking control method of the PTZ camera according to the present invention includes a step of identifying a plurality of adjacent video blocks (hereinafter referred to as 'neighbor block') around the moving object area; B) comparing a motion vector value with a second preset threshold value for a plurality of neighboring blocks; C) additionally marking a neighboring block having a motion vector value exceeding a second threshold as a moving object region; D) additionally marking a neighboring block having a coding type of an intra picture among the plurality of neighboring blocks as a moving object region; The method may further include an e-step of performing interpolation on the plurality of moving object regions to additionally mark a predetermined number or less of unmarked image blocks surrounded by the moving object region as the moving object region.

In the present invention, the seventh step may be configured to perform panning and tilting control on the PTZ camera so that the tracked moving object region is located at a preset observation point in the compressed image. In addition, the eighth step of the present invention may be configured to perform a zoom control on the PTZ camera so that the tracking target moving object region is a preset observation size in the compressed image.

On the other hand, the computer program according to the present invention is stored in the medium in order to execute the object tracking control method of the syntax-based PTZ camera for the compressed image as described above combined with hardware.

According to the present invention, an object tracking control of a PTZ camera can be performed by identifying a moving object region from a CCTV compressed image without performing complicated processing such as decoding, downscale resizing, difference image acquisition, image analysis, and the like. In particular, the object tracking control of the PTZ camera is possible even with a calculation amount of about 1/20 compared with the prior art, and thus, there is an advantage in that the number of PTZ camera accommodation channels of the CCTV control system can be greatly increased without large-scale investment.

1 is a block diagram showing a general configuration of a video decoding apparatus.

Figure 2 is a flow chart showing the object tracking control process of the PTZ camera made in the prior art.

3 is a flowchart illustrating an object tracking control process of a PTZ camera according to the present invention.

4 is a flowchart illustrating an embodiment of a process of detecting effective motion from a compressed image in the present invention.

5 is a diagram illustrating an example of a result of applying an effective motion region detection process according to the present invention to a CCTV compressed image.

FIG. 6 is a flowchart illustrating an example of a process of detecting a boundary region for a moving object region in the present invention. FIG.

7 is a diagram illustrating an example of a result of applying a boundary area detection process according to the present invention to the CCTV image of FIG.

8 is a diagram illustrating an example of a result of arranging a moving object region through interpolation with respect to the CCTV image of FIG. 7.

FIG. 9 is a flowchart illustrating an embodiment of a process of controlling an object to control a PTZ camera with respect to a moving object region to be tracked in the present invention.

FIG. 10 is a diagram for one example in which a unique ID is assigned to a moving object area in the present invention; FIG.

FIG. 11 illustrates an example in which size information is identified in a moving object area in the present invention. FIG.

12 is a diagram illustrating an example in which location information is identified in a moving object area in the present invention.

Hereinafter, with reference to the drawings will be described in detail the present invention.

3 is a flowchart illustrating an object tracking control process of a PTZ camera according to the present invention. The object tracking control process of the PTZ camera according to the present invention may be performed by an image analysis server which processes a compressed image generated by a PTZ camera in a system that processes a series of compressed images, for example, a CCTV control system.

According to the present invention, syntax information obtained for each image block, that is, a macro block and a sub block, by parsing a bitstream of the compressed image without decoding the compressed image, for example, a motion vector, Quickly extract moving object region through coding type information. The moving object area thus obtained does not accurately reflect the boundary of the moving object, but the processing speed is high and the reliability is higher than a certain level. Then, for example, if a CCTV controller designates a specific moving object area, the moving object area can be tracked by panning, tilting, and zooming the PTZ camera based on the size and position of the moving object area (e.g., center coordinates). To perform the operation.

Meanwhile, according to the present invention, the moving object region can be extracted and the object tracking can be performed without decoding the compressed image. However, the apparatus or software to which the present invention is applied should not perform the operation of decoding the compressed image, but the scope of the present invention is not limited.

Hereinafter, a concept of a process of performing object tracking by a PTZ camera according to the present invention will be described with reference to FIG. 3.

Step S100: First, an effective motion that can be substantially recognized from the compressed image is detected from the compressed image based on the motion vector of the compressed image, and the image region in which the effective motion is detected is set as the moving object region.

To this end, data of a compressed image is parsed according to video compression standards such as H.264 AVC and H.265 HEVC to obtain a motion vector and a coding type for a coding unit. In this case, the size of the coding unit is generally about 64x64 to 4x4 pixels and may be set to be flexible.

The motion vectors are accumulated for a predetermined time period (for example, 500 msec) for each image block, and it is checked whether the motion vector accumulation value exceeds the first predetermined threshold (for example, 20). If such an image block is found, it is considered that effective motion has been found in the image block and marked as a moving object area. Accordingly, even if the motion vector is generated, if the cumulative value for a predetermined time does not exceed the first threshold, the image change is assumed to be insignificant and ignored.

Step S200: Detects how far the boundary region is to the moving object region detected in S100 based on the motion vector and the coding type. If a motion vector occurs above a second threshold (for example, 0) or a coding type is an intra picture by inspecting a plurality of adjacent image blocks centered on the image block marked as a moving object area, the corresponding image block is also moved. Mark as an object area. Through this process, the corresponding image block is substantially in the form of forming a lump with the moving object region detected in S100.

If an effective motion is found and there is a certain amount of motion in the vicinity of the moving object area, it is marked as a moving object area because it is likely to be a mass with the previous moving object area. In addition, in the case of an intra picture, since a motion vector does not exist, determination based on a motion vector is impossible. Accordingly, the intra picture located adjacent to the image block already detected as the moving object region is estimated as a mass together with the previously extracted moving object region.

Step S300: The interpolation is applied to the moving object areas detected at S100 and S200 to clean up the fragmentation of the moving object area. In the above process, since it is determined whether the moving object area is the image block unit, even though it is actually a moving object (for example, a person), there is an image block that is not marked as the moving object area in the middle. The phenomenon of dividing into may occur. Accordingly, if there are one or a few unmarked image blocks surrounded by a plurality of image blocks marked with the moving object region, they additionally mark the moving object region. By doing so, it is possible to make the mobile object region divided into several into one. The influence of such interpolation is clearly seen when comparing FIG. 7 and FIG.

Step S400: The moving object region is quickly extracted from each frame image constituting the compressed image based on the syntax (motion vector, coding type) of the coding unit through the above process. Next, in steps S400 to S700, when a specific moving object region is identified as a target, object tracking control for the PTZ camera is performed using the extraction result of the moving object region.

First, a specific moving object region is identified as a tracking target among one or more moving object regions identified in the above process, which is referred to herein as a 'tracking target moving object region'. The tracking object area may be implemented so that the control personnel can designate the control agent through a mouse operation or the like on the CCTV video control screen, or may be implemented so that the video control software discovers itself according to the identification condition set through the menu of the video control software. .

Step S500: Obtain location information and size information of the area to be tracked in the current frame image. 11 and 12 illustrate examples in which size information and position information are identified for a moving object region. The location information means a location in the image of the corresponding video block. The location information may be set as the upper left coordinate as shown in FIG. 11 or may be set as the center coordinate as shown in FIG. 12. As the size information, as shown in FIG. 11, a size of a rectangle that optimally surrounds a moving object area may be set.

Step S600: Panning and tilting control of the PTZ camera is performed by using the location information of the tracking target moving object region. Panning and tilting control is performed on the PTZ camera so that the moving object area to be tracked is located at a preset observation point (for example, the center of the recording screen) in the CCTV image. For example, when the moving object region indicated by Unique ID = 001 in FIG. 11 is set as the tracking target moving object region, 30 degrees panning control and 10 degrees tilting control upward for the PTZ camera are performed. In addition, when the moving object region indicated by Unique ID = 003 in FIG. 11 is set as the tracking target moving object region, the panning control is performed 7 degrees in the clockwise direction (CW) and the tilting control is 5 degrees downward.

Step S700: In addition, zoom control of the PTZ camera is performed by using the size information of the tracked moving object region. Zoom control is performed on the PTZ camera so that the tracking object area becomes a preset observation size (eg, 50% of the entire screen) in the CCTV image. For example, when the moving object region indicated by Unique ID = 001 in FIG. 11 is set as the tracking target moving object region, 500% zoom control is performed on the PTZ camera. In addition, if the moving object region indicated by Unique ID = 003 in FIG. 11 is set as the tracking target moving object region, 200% zoom control is performed on the PTZ camera.

In the present invention, a process of performing object tracking control of the PTZ camera based on the syntax of the compressed image will be described in detail with reference to FIGS. 4 to 12. First, a process of identifying a moving object region by syntax from a compressed image will be described in detail with reference to FIGS. 4 to 8. In addition, a process of using the identified moving object area for object tracking control for the PTZ camera will be described in detail with reference to FIGS. 9 to 12.

4 is a flowchart illustrating an example of a process of detecting effective motion from a compressed image in the present invention, and FIG. 5 is a diagram illustrating an example of a result of applying the effective motion region detection process according to the present invention to a CCTV compressed image. . The process of FIG. 4 corresponds to step S100 in FIG. 3.

Step S110: First, a coding unit of a compressed image is parsed to obtain a motion vector and a coding type. Referring to FIG. 1, a video decoding apparatus performs parsing (header parsing) and motion vector operations on a stream of compressed video according to a video compression standard such as H.264 AVC and H.265 HEVC. Through this process, the motion vector and coding type are parsed for the coding unit of the compressed image.

Step S120: Next, a global motion vector is subtracted for each motion vector. In this specification, the global motion vector means an average value of all motion vectors obtained from the corresponding frame. Preferably, a value obtained by summing the motion vectors acquired in the frame and dividing by the total number of image blocks belonging to the frame may be set as the global motion vector.

While the PTZ camera is changing one or more of panning, tilting, and zooming, the captured image changes as a whole depending on the specific orientation. In this case, since the motion vector is derived for most image blocks, the global motion vector is obtained with a significant value and reflects the directivity of the entire captured image. By subtracting the global motion vector for each motion vector, the motion vector obtained by the PTZ operation is canceled and the motion vector remains with the direction removed from the whole image by the PTZ operation only for the image block with purely moving contents. . This allows the PTZ camera to extract and track moving objects while panning, tilting and zooming.

On the other hand, while the PTZ camera is still without panning, tilting, or zooming, the global motion vector should not have any effect. During this time, only a few image blocks are derived from the captured image, and most of the image blocks do not derive the motion vector. In this case, since the global motion vector is obtained with a very small value close to 0, subtracting the global motion vector for each motion vector does not have a significant effect.

Step S130: Acquire a motion vector cumulative value for a preset time (for example, 500 ms) for each of the plurality of image blocks constituting the compressed image.

This step is presented with the intention to detect if there are effective movements that are practically recognizable from the compressed image, such as driving cars, running people, and fighting crowds. Shaky leaves, ghosts that appear momentarily, and shadows that change slightly due to light reflections, though they are moving, are virtually meaningless objects and should not be detected.

To this end, a motion vector cumulative value is obtained by accumulating a motion vector in units of one or more image blocks for a predetermined time period (for example, 500 msec). In this case, the image block is used as a concept including a macroblock and a subblock.

Steps S140 and S150: Comparing a motion vector cumulative value with respect to a plurality of video blocks with a preset first threshold value (eg, 20), and moving the image block having a motion vector cumulative value exceeding the first threshold value. Mark with

If an image block having a predetermined motion vector accumulation value is found as described above, it is considered that something significant movement, that is, effective movement, is found in the image block and is marked as a moving object region. For example, in a video surveillance system, a human run is to select and detect a movement that is worth the attention of the control personnel. On the contrary, even if a motion vector is generated, if the cumulative value for a predetermined time is small enough not to exceed the first threshold, the change in the image is assumed to be small and insignificant and is neglected in the detection step.

FIG. 5 is an example illustrating a result of detecting an effective motion region from a CCTV compressed image through the process of FIG. 4. In FIG. 5, an image block having a motion vector accumulation value equal to or greater than a first threshold is marked as a moving object area and displayed as a bold line area. Referring to FIG. 5, the sidewalk block, the road, and the shadowed part are not displayed as the moving object area, while the walking people or the driving car are displayed as the moving object area.

FIG. 6 is a flowchart illustrating an example of a process of detecting a boundary region of a moving object region in the present invention, and FIG. 7 is a boundary region of FIG. 5 with respect to the CCTV image of FIG. Figure 1 shows an example of the results of further applying the detection process. The process of FIG. 6 corresponds to step S200 in FIG. 3.

Referring to FIG. 5, it can be found that the moving object is not properly marked and only a portion of the moving object is marked. In other words, if you look at a person walking or driving a car, you will find that not all of the objects are marked, but only some blocks. In addition, it is also found that a plurality of moving object areas are marked for one moving object. This means that the criterion of the moving object region adopted in (S100) above was useful for filtering out the general region but was a very strict condition. Therefore, it is necessary to detect the boundary of the moving object by looking around the moving object area.

Step S210: First, a plurality of adjacent image blocks are identified based on the image blocks marked as moving object areas by the previous S100. In the present specification, these are referred to as 'neighborhood blocks'. These neighboring blocks are portions that are not marked as the moving object region by S100, and the process of FIG. 6 examines them further to determine whether any of these neighboring blocks may be included in the boundary of the moving object region.

Steps S220 and S230: compare a motion vector value with respect to a plurality of neighboring blocks with a second preset threshold (eg, 0), and mark the neighboring block having a motion vector value exceeding the second threshold as a moving object region. do. If the movement is located adjacent to the area of the moving object where effective motion that is practically meaningful is found and a certain amount of movement is found for itself, the image block is likely to be a block with the area of the adjacent moving object due to the characteristics of the photographed image. . Therefore, such neighboring blocks are also marked as moving object regions.

Step S240: Also, the coding type is an intra picture among the plurality of neighboring blocks as a moving object region. In the case of an intra picture, since a motion vector does not exist, it is fundamentally impossible to determine whether a motion exists in a corresponding neighboring block based on the motion vector. In this case, it is safer for the intra picture located adjacent to the image block already detected as the moving object region to maintain the settings of the previously extracted moving object region.

FIG. 7 is a diagram visually illustrating a result of applying a boundary region detection process to a CCTV compressed image. A plurality of image blocks marked as a moving object region through the above process are indicated by a bold line. Referring to FIG. 7, it was found that the moving object area was further extended to the vicinity of the moving object area indicated by the bold line area in FIG. 5, so that the moving object area was covered enough to be compared with the image taken by CCTV. can do.

FIG. 8 is a diagram illustrating an example of a result of arranging a moving object region through interpolation according to the present invention for a CCTV image image to which the boundary region detection process illustrated in FIG. 7 is applied.

Step S300 is a process of arranging the division of the moving object area by applying interpolation to the moving object areas detected in the previous steps S100 and S200. Referring to FIG. 7, an unmarked image block is found between the moving object regions indicated by the bold lines. If there is an unmarked image block in the middle, it can be regarded as if they are a plurality of individual moving objects. When the moving object region is fragmented in this way, the result of step S500 may be inaccurate, and the number of moving object regions may increase, thereby complicating the process of steps S500 to S700.

Accordingly, in the present invention, if there is one or a few unmarked image blocks surrounded by a plurality of image blocks marked as the moving object region, this is marked as the moving object region, which is called interpolation. Referring to FIG. 8, in contrast to FIG. 7, all of the non-marked image blocks existing between the moving object regions are marked as moving object regions. As a result, it is possible to derive a more intuitive and accurate moving object detection result for the control personnel to refer to.

Comparing FIG. 5 and FIG. 8, it can be found that the moving object region properly reflects the actual image situation through the boundary region detection process and the interpolation process. In FIG. 5, if the block is marked as a bold line region, a large number of very small objects are moved as if moving in the image screen, which is inconsistent with reality. On the other hand, if it is determined as a block marked with the bold line area in Fig. 8 will be treated as a few moving objects having a certain volume to reflect the actual scene similarly.

FIG. 9 is a flowchart illustrating an example of a process of tracking and tracking an object of a PTZ camera with respect to a moving object region to be tracked in the present invention, and corresponds to steps S500 to S700 in FIG. 3.

As described above, the present invention extracts a moving object region based on syntax information directly obtained from a compressed image. The process of acquiring and analyzing the difference image with respect to the original image by decoding the compressed image of the prior art is unnecessary, and according to the inventor's test, the processing speed is improved up to 20 times. However, this approach has the disadvantage of poor precision. There is a difference in concept in that it extracts the chunk of the image block that is assumed to contain the moving object, rather than extracting the moving object. In the present invention, this feature is also reflected in the process of tracking an object based on the moving object area of the PTZ camera.

Hereinafter, an embodiment of an object tracking control process of a PTZ camera adopted in the present invention will be described in detail.

Step S410: First, a unique ID is managed for a moving object region extracted based on a syntax from a compressed image. The moving object region is derived from each image frame constituting the compressed image. This is not a result of analyzing the image content and determining that it is an object, but a concept of a chunk of an image that seems to be moving in the image frame.

However, in the present invention, since the PTZ camera needs to be panned, tilted, and zoomed while following a specific object, the moving object region set as the tracking target in the previous frame must be continuously identified in the next frame when the image frame is advanced. In other words, you need to go beyond the idea of a chunk of an image in that frame and treat it like an object. Therefore, by assigning and managing a unique ID for the moving object region derived from the compressed image, the moving object region can be treated like an object rather than a region, and the compressed image is passed over a series of frame images. You can track the movement of a specific object.

Unique ID management of the mobile object area is handled in the following three cases. If a unique ID is assigned in the previous frame and the current frame image identifies a moving object region that is assigned an ID (S411), the moving object region identified as an unassigned ID in the current frame image because it has never been identified in the previous frame. In the case of newly assigning a unique ID to the SID, a mobile object region in which a unique ID is allocated in the previous frame but disappeared from the current frame image is identified and revokes the allocated unique ID (S413).

However, in a series of frame images constituting the compressed image, it should be possible to determine whether the chunk of the image block marked as the moving object region in the previous frame is related to the same object between front and rear frames. This is because it is possible to determine whether the Unique ID has been previously assigned to the moving object area handled in the current frame.

In the present invention, since only the image block is a moving object region without checking the contents of the original image, it is not possible to confirm whether the chunks of the moving object region are actually the same in the image frames before and after. That is, since the contents of the moving object area are not known, such a change cannot be identified, for example, when the cat is replaced by a dog between the front and rear frames at the same point. However, considering that the time interval between frames is very short and that the observation object of the CCTV camera moves at a normal speed, the possibility of this happening can be excluded.

Accordingly, the present invention estimates that the ratio or number of image blocks overlapping between the chunks of the moving object region in the front and back frames is equal to or greater than a predetermined threshold. According to this approach, even if the contents of the image are not known, it is possible to determine whether the previously identified moving object region is moved or whether a new moving object region is newly discovered or the existing moving object region is lost. This judgment is lower in accuracy than the prior art, but can greatly increase the data processing speed, which is advantageous in practical applications.

In step S411, when the moving object region to which the Unique ID has been assigned in the previous frame is identified in the current frame image, the previously allocated Unique ID is allocated to the corresponding moving object region. According to the implementation example, the identification may be marked in the management database of the Unique ID.

In step S412, if a new object is unidentified in the current frame image because it has not been identified in the previous frame, a unique ID is newly assigned to the mobile object region. This means that a new moving object is found in the image. 11 and 12 illustrate examples in which unique IDs are allocated to three moving object areas in a CCTV photographing image.

In step S413, when the moving object region in which the unique ID is assigned in the previous frame of the compressed image disappears from the current frame image, the moving object region is allocated in step S412 with respect to the previous frame for the moving object region. Revoke unique ID maintained in S411). In other words, the moving object that has been discovered and managed before has disappeared from the image.

Step S420: In step S400 of FIG. 3, a specific moving object region is set as the tracking target moving object region in the CCTV photographed image by, for example, a mouse operation of a controller. The tracked moving object region may be set in the current frame or may be set in the previous frame.

Accordingly, in step S420, a unique ID assigned to the tracked moving object region is identified in the current frame image, which is sometimes referred to as 'tracking unique ID'. The unique ID is allocated and managed through the operation S410 for the moving object region identified in each frame image in the process of processing the frame image one by one in the compressed image. The unique ID is managed by classifying the moving object area identified in the previous frame, the moving object area newly identified in the current frame, and the moving object area identified in the previous frame but disappearing from the current frame. Accordingly, the unique ID of the tracking target object region may be identified unless the tracking target object region disappears from the current frame.

Steps S430 to S450: Derived the position information and the size information of the moving object region to which the tracking target Unique ID value is allocated in the current frame image, which corresponds to step S500 of FIG. 3. 11 and 12 illustrate examples in which size information and position information are identified for a moving object region. The location information means a location in the image of the corresponding video block. The location information may be set as the upper left coordinate as shown in FIG. 11 or may be set as the center coordinate as shown in FIG. 12. As the size information, as shown in FIG. 11, a size of a rectangle that optimally surrounds a moving object area may be set.

Next, panning and tilting control of the PTZ camera is performed using the location information of the tracking target moving object region, and zoom control of the PTZ camera is performed using the size information of the tracking target moving object region. This process has been described above in steps S600 and S700 of FIG. 3.

Meanwhile, the present invention may be embodied in the form of computer readable codes on a computer readable nonvolatile recording medium. Such nonvolatile recording media include various types of storage devices, such as hard disks, SSDs, CD-ROMs, NAS, magnetic tapes, web disks, and cloud disks. Forms that are implemented and executed may also be implemented. In addition, the present invention may be implemented in the form of a computer program stored in a medium in combination with hardware to execute a specific procedure.

Claims

Parsing the bitstream of the compressed image to obtain a motion vector and a coding type for the coding unit;

A second step of obtaining a motion vector cumulative value for a first preset time for each of the plurality of image blocks constituting the compressed image;

A third step of comparing the motion vector cumulative value with a first threshold value for the plurality of image blocks;

A fourth step of marking an image block having a motion vector accumulation value exceeding the first threshold as a moving object region;

A fifth step of identifying a tracking target object region to be tracked by a PTZ camera among the at least one marked moving object region;

A sixth step of acquiring position information and size information of the tracked moving object region from a current frame image;

A seventh step of performing panning and tilting control with respect to the PTZ camera based on the position information of the area to be tracked;

An eighth step of performing zoom control on the PTZ camera by using the size information of the area to be tracked;

Object tracking control method of the syntax-based PTZ camera for the compressed image comprising a.
The method according to claim 1,

Performed between the first step and the second step,

Calculating a global motion vector corresponding to an average value of the motion vectors for each frame;

Subtracting the global motion vector calculated for the frame with respect to the motion vector;

Object tracking control method of the syntax-based PTZ camera for the compressed image further comprises a.
The method according to claim 2,

And the global motion vector is calculated by summing all motion vectors acquired in the frame and dividing by the total number of image blocks belonging to the frame.
The method according to claim 1,

The seventh step may be configured to perform panning and tilting control on the PTZ camera so that the tracking target moving object region is located at a preset observation point in the compressed image. Tracking control method.
The method according to claim 4,

The eighth step may be configured to perform zoom control on the PTZ camera such that the area of the tracking target moving object is set to a preset observation size in the compressed image. .
The method according to claim 1,

Performed between the fourth and fifth steps,

A step of identifying a plurality of adjacent image blocks (hereinafter, referred to as 'neighbor block') around the moving object area;

B) comparing a motion vector value obtained in the first step with respect to the plurality of neighboring blocks with a second preset threshold value;

C) additionally marking, as a moving object region, a neighboring block having a motion vector value exceeding the second threshold value as a result of the comparison in the b of the plurality of neighboring blocks;

Object tracking control method of the syntax-based PTZ camera for the compressed image further comprises a.
The method according to claim 6,

Carried out after the step c,

D) additionally marking a neighboring block having a coding type of an intra picture among the plurality of neighboring blocks as a moving object region;

Object tracking control method of the syntax-based PTZ camera for the compressed image further comprises a.
The method according to claim 6,

Carried out after the d step,

Performing an interpolation operation on the plurality of moving object regions to additionally mark up to a predetermined number of non-marked image blocks surrounded by the moving object region as a moving object region;

Object tracking control method of the syntax-based PTZ camera for the compressed image further comprises a.
A computer program stored in a medium in combination with hardware for executing an object tracking control method of a syntax based PTZ camera for a compressed image according to any one of claims 1 to 8.