CN107066931A - A kind of target trajectory tracking based on monitor video - Google Patents
A kind of target trajectory tracking based on monitor video Download PDFInfo
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- CN107066931A CN107066931A CN201710023293.9A CN201710023293A CN107066931A CN 107066931 A CN107066931 A CN 107066931A CN 201710023293 A CN201710023293 A CN 201710023293A CN 107066931 A CN107066931 A CN 107066931A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/48—Matching video sequences
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/49—Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes
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Abstract
This application discloses a kind of target trajectory tracking based on monitor video, including：The first frame video in s1, acquisition monitoring video：S2, the image in the first frame video is pre-processed, label is marked to the moving target in the frame video image：S3, extract and record current video frame number, and target labels center-of-mass coordinate, boundary rectangle and profile parameters：Next frame video in s4, acquisition monitoring video, extracts and records current video frame number, and target labels center-of-mass coordinate, boundary rectangle, profile parameters, the direction of motion and movement velocity：S5, the next frame video continued in acquisition monitoring video, characteristic matching is carried out with the target of former frame：S6, specific objective label track is tracked.The present invention not only records the positional information of moving target in each frame video, is also recorded for boundary rectangle, profile parameters, the direction of motion and the motion velocity information of moving target, can more accurately capture movement target movement locus.
Description
Technical field
The application is related to technical field of video monitoring, more particularly to a kind of target trajectory track side based on monitor video
Method.
Background technology
With developing rapidly for electronic technology and information technology, video monitoring system start to be widely used in army, bank,
The places such as shop, parking lot, residential area, traffic intersection, commercial building, when the generation theft of these places, pursuit, delay etc. are different
When Chang Hangwei occurs, video monitoring can accurately and timely tackle the strong help of offer for guard, can also occur in event
There is provided investigating and collecting evidence and support energetically afterwards, to ensure that the normal operation of society and public place is made that tremendous contribution.
In traditional means, the extraction to track often only obtains the positional information of each moving target in each frame video,
The attribute of target each side itself is not recorded, it is difficult to accurately acquire the track of target.
The content of the invention
It is an object of the invention to provide a kind of target trajectory tracking based on monitor video, to overcome prior art
In deficiency.
To achieve the above object, the present invention provides following technical scheme：
The embodiment of the present application discloses a kind of target trajectory tracking based on monitor video, including step：
The first frame video in s1, acquisition monitoring video；
S2, the image in the first frame video is pre-processed, the moving target in the frame video image is marked
Label；
S3, extract and record current video frame number, and target labels center-of-mass coordinate, boundary rectangle and profile ginseng
Number；
Next frame video in s4, acquisition monitoring video, extracts and records current video frame number, and target labels
Center-of-mass coordinate, boundary rectangle, profile parameters, the direction of motion and movement velocity；
S5, the next frame video continued in acquisition monitoring video, extract and record current video frame number, and target mark
Center-of-mass coordinate, boundary rectangle, profile parameters, the direction of motion and the movement velocity of label, characteristic matching is carried out with the target of former frame,
If the match is successful, the target sequence number is labeled as the target labels matched in former frame, and matching target is added into tracking row
Table is preserved, otherwise, for the new label of the target label；
S6, specific objective label track is tracked.
It is preferred that, in the above-mentioned target trajectory tracking based on monitor video, using bivector
The center-of-mass coordinate of target labels is represented, and is met：
Wherein, W, H represent the wide and height of moving target circumscribed rectangular region respectively, and (x, y) is the picture point of target labels
Coordinate, M (x, y) is met：
It is assumed that the i-th frame and each pixel gray value of jth two field picture are respectively f (x, y, i) and f (x, y, j) in video image,
Then difference image is represented：
Dif (x, y, i, j)=| f (x, y, i)-f (x, y, j) |
The threshold value T of setting, extracts moving region in video image：
It is preferred that, in the above-mentioned target trajectory tracking based on monitor video, using the target upper left corner and bottom right
The coordinate on angle Liang Ge summits represents target boundary rectangle.
It is preferred that, in the above-mentioned target trajectory tracking based on monitor video, the boundary rectangle using 4 tie up to
Amount storage.
It is preferred that, in the above-mentioned target trajectory tracking based on monitor video, the pretreatment includes：Video flowing
Pretreatment, background modeling, foreground segmentation and elimination shade.
It is preferred that, in the above-mentioned target trajectory tracking based on monitor video, the video flowing pretreatment includes
Denoising, adjustment frame per second and frame sign.
Compared with prior art, the advantage of the invention is that：The present invention not only records moving target in each frame video
Positional information, is also recorded for boundary rectangle, profile parameters, the direction of motion and the motion velocity information of moving target, can be more
The accurately movement locus of capture movement target.
Embodiment
The technical scheme in the embodiment of the present invention will be described in detail below, it is clear that described embodiment is only
Only it is a part of embodiment of the invention, rather than whole embodiments.Based on the embodiment in the present invention, ordinary skill
The every other embodiment that personnel are obtained on the premise of creative work is not made, belongs to the model that the present invention is protected
Enclose.
Present embodiment discloses a kind of target trajectory tracking based on monitor video, including step：
The first frame video in s1, acquisition monitoring video；
S2, the image in the first frame video is pre-processed, the moving target in the frame video image is marked
Label；
S3, extract and record current video frame number, and target labels center-of-mass coordinate, boundary rectangle and profile ginseng
Number；
Next frame video in s4, acquisition monitoring video, extracts and records current video frame number, and target labels
Center-of-mass coordinate, boundary rectangle, profile parameters, the direction of motion and movement velocity；
S5, the next frame video continued in acquisition monitoring video, extract and record current video frame number, and target mark
Center-of-mass coordinate, boundary rectangle, profile parameters, the direction of motion and the movement velocity of label, characteristic matching is carried out with the target of former frame,
If the match is successful, the target sequence number is labeled as the target labels matched in former frame, and matching target is added into tracking row
Table is preserved, otherwise, for the new label of the target label；
S6, specific objective label track is tracked.
Using bivectorThe center-of-mass coordinate of target labels is represented, and is met：
Wherein, W, H represent the wide and height of moving target circumscribed rectangular region respectively, and (x, y) is the picture point of target labels
Coordinate, M (x, y) is met：
It is assumed that the i-th frame and each pixel gray value of jth two field picture are respectively f (x, y, i) and f (x, y, j) in video image,
I, j take positive integer, then difference image is represented：
Dif (x, y, i, j)=| f (x, y, i)-f (x, y, j) |
The threshold value T of setting, extracts moving region in video image：
In the technical scheme, video frame number can be recorded while video is read；Using the target upper left corner and the right side
The coordinate on two summits of inferior horn represents target boundary rectangle, and boundary rectangle is preferred to use the storage of 4 dimensional vectors.
In the technical scheme, pretreatment includes：Video flowing pretreatment, background modeling, foreground segmentation and elimination shade.Its
In, video flowing pretreatment includes denoising, adjustment frame per second and frame sign.
In the technical scheme, in detection process of moving target, objective contour can be obtained, it is general using a long array
To store.
In the technical scheme, target direction of motion and movement velocity must could be obtained after target association is completed, this
Case represents target speed, the pixel that the direction of motion is then moved with barycenter in X-direction using the pixel number moved per frame
Point is represented with the bivector of the pixel number composition of Y-direction movement.
It should be noted that herein, term " comprising ", "comprising" or its any other variant are intended to non-row
His property is included, so that process, method, article or equipment including a series of key elements not only include those key elements, and
And also including other key elements being not expressly set out, or also include for this process, method, article or equipment institute inherently
Key element.In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that including institute
Also there is other identical element in process, method, article or the equipment of stating key element.
Described above is only the embodiment of the application, it is noted that for the ordinary skill people of the art
For member, on the premise of the application principle is not departed from, some improvements and modifications can also be made, these improvements and modifications also should
It is considered as the protection domain of the application.
Claims (6)
1. a kind of target trajectory tracking based on monitor video, it is characterised in that including step：
The first frame video in s1, acquisition monitoring video；
S2, the image in the first frame video is pre-processed, label is marked to the moving target in the frame video image；
S3, extract and record current video frame number, and target labels center-of-mass coordinate, boundary rectangle and profile parameters；
Next frame video in s4, acquisition monitoring video, extracts and records current video frame number, and target labels barycenter
Coordinate, boundary rectangle, profile parameters, the direction of motion and movement velocity；
S5, the next frame video continued in acquisition monitoring video, extract and record current video frame number, and target labels
Center-of-mass coordinate, boundary rectangle, profile parameters, the direction of motion and movement velocity, characteristic matching is carried out with the target of former frame, if
The match is successful, then the target sequence number is labeled as the target labels matched in former frame, and matching target is added into tracking list protects
Deposit, otherwise, for the new label of the target label；
S6, specific objective label track is tracked.
2. the target trajectory tracking according to claim 1 based on monitor video, it is characterised in that：Using two dimension to
AmountThe center-of-mass coordinate of target labels is represented, and is met：
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<mo>=</mo>
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</mrow>
</munderover>
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</mrow>
<mrow>
<mi>H</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mi>x</mi>
<mi>M</mi>
<mrow>
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<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
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</mrow>
</mrow>
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<mo>&Sigma;</mo>
<mrow>
<mi>x</mi>
<mo>=</mo>
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</mrow>
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</mrow>
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<mn>1</mn>
</mrow>
</munderover>
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<mi>x</mi>
<mo>,</mo>
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<mo>)</mo>
</mrow>
</mrow>
</mfrac>
</mrow>
Wherein, W, H represent the wide and height of moving target circumscribed rectangular region respectively, and (x, y) is the image point coordinates of target labels,
M (x, y) is met：
It is assumed that the i-th frame and each pixel gray value of jth two field picture are respectively f (x, y, i) and f (x, y, j) in video image, then it is poor
Partial image is represented：
Dif (x, y, i, j)=| f (x, y, i)-f (x, y, j) |
The threshold value T of setting, extracts moving region in video image：
<mrow>
<mi>M</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
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<mfenced open='{' close=''>
<mtable>
<mtr>
<mtd>
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</mrow>
<mo>&GreaterEqual;</mo>
<mi>T</mi>
</mtd>
</mtr>
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</mfenced>
<mo>.</mo>
</mrow>
3. the target trajectory tracking according to claim 1 based on monitor video, it is characterised in that：It is left using target
The coordinate on upper angle and the lower right corner Liang Ge summits represents target boundary rectangle.
4. the target trajectory tracking according to claim 3 based on monitor video, it is characterised in that：The external square
Shape is stored using 4 dimensional vectors.
5. the target trajectory tracking according to claim 1 based on monitor video, it is characterised in that：The pretreatment
Including：Video flowing pretreatment, background modeling, foreground segmentation and elimination shade.
6. the target trajectory tracking according to claim 5 based on monitor video, it is characterised in that：The video flowing
Pretreatment includes denoising, adjustment frame per second and frame sign.
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Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107833240A (en) * | 2017-11-09 | 2018-03-23 | 华南农业大学 | The target trajectory extraction of multi-track clue guiding and analysis method |
| CN108182696A (en) * | 2018-01-23 | 2018-06-19 | 四川精工伟达智能技术股份有限公司 | Image processing method, device and Multi-target position tracking system |
| CN108229456A (en) * | 2017-11-22 | 2018-06-29 | 深圳市商汤科技有限公司 | Method for tracking target and device, electronic equipment, computer storage media |
| CN108225735A (en) * | 2018-01-09 | 2018-06-29 | 北京航空航天大学 | A kind of precision approach indicator flight check method of view-based access control model |
| CN108897899A (en) * | 2018-08-23 | 2018-11-27 | 深圳码隆科技有限公司 | The localization method and its device of the target area of a kind of pair of video flowing |
| CN109087510A (en) * | 2018-09-29 | 2018-12-25 | 讯飞智元信息科技有限公司 | traffic monitoring method and device |
| CN109118516A (en) * | 2018-07-13 | 2019-01-01 | 高新兴科技集团股份有限公司 | A kind of target is from moving to static tracking and device |
| CN109215393A (en) * | 2018-11-20 | 2019-01-15 | 中国葛洲坝集团公路运营有限公司 | A kind of method and system for the monitoring of target area anomalous event |
| CN109243150A (en) * | 2018-09-30 | 2019-01-18 | 深圳市金豪泰科技有限公司 | A kind of vehicle early warning method and terminal |
| CN109615862A (en) * | 2018-12-29 | 2019-04-12 | 南京市城市与交通规划设计研究院股份有限公司 | Road vehicle movement of traffic state parameter dynamic acquisition method and device |
| CN110598559A (en) * | 2019-08-15 | 2019-12-20 | 深圳和而泰家居在线网络科技有限公司 | Method and device for detecting motion direction, computer equipment and storage medium |
| CN111579466A (en) * | 2020-05-25 | 2020-08-25 | 上海师范大学 | Household sperm detection device and detection method |
| CN111968159A (en) * | 2020-08-28 | 2020-11-20 | 厦门大学 | Simple and universal fish video image track tracking method |
| CN112492196A (en) * | 2020-10-29 | 2021-03-12 | 贝壳技术有限公司 | Live broadcast in-process anchor tracking method, device and system |
| CN114419097A (en) * | 2021-12-30 | 2022-04-29 | 西安天和防务技术股份有限公司 | Target tracking method and device |
| CN115588154A (en) * | 2022-10-11 | 2023-01-10 | 湖北中医药大学 | System and method for recognizing and transcribing motion trail of acupuncture manipulation |
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Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107833240A (en) * | 2017-11-09 | 2018-03-23 | 华南农业大学 | The target trajectory extraction of multi-track clue guiding and analysis method |
| CN107833240B (en) * | 2017-11-09 | 2020-04-17 | 华南农业大学 | Target motion trajectory extraction and analysis method guided by multiple tracking clues |
| CN108229456A (en) * | 2017-11-22 | 2018-06-29 | 深圳市商汤科技有限公司 | Method for tracking target and device, electronic equipment, computer storage media |
| CN108225735A (en) * | 2018-01-09 | 2018-06-29 | 北京航空航天大学 | A kind of precision approach indicator flight check method of view-based access control model |
| CN108182696A (en) * | 2018-01-23 | 2018-06-19 | 四川精工伟达智能技术股份有限公司 | Image processing method, device and Multi-target position tracking system |
| CN109118516A (en) * | 2018-07-13 | 2019-01-01 | 高新兴科技集团股份有限公司 | A kind of target is from moving to static tracking and device |
| CN108897899A (en) * | 2018-08-23 | 2018-11-27 | 深圳码隆科技有限公司 | The localization method and its device of the target area of a kind of pair of video flowing |
| CN109087510A (en) * | 2018-09-29 | 2018-12-25 | 讯飞智元信息科技有限公司 | traffic monitoring method and device |
| CN109243150A (en) * | 2018-09-30 | 2019-01-18 | 深圳市金豪泰科技有限公司 | A kind of vehicle early warning method and terminal |
| CN109215393A (en) * | 2018-11-20 | 2019-01-15 | 中国葛洲坝集团公路运营有限公司 | A kind of method and system for the monitoring of target area anomalous event |
| CN109615862A (en) * | 2018-12-29 | 2019-04-12 | 南京市城市与交通规划设计研究院股份有限公司 | Road vehicle movement of traffic state parameter dynamic acquisition method and device |
| CN110598559A (en) * | 2019-08-15 | 2019-12-20 | 深圳和而泰家居在线网络科技有限公司 | Method and device for detecting motion direction, computer equipment and storage medium |
| CN111579466A (en) * | 2020-05-25 | 2020-08-25 | 上海师范大学 | Household sperm detection device and detection method |
| CN111968159A (en) * | 2020-08-28 | 2020-11-20 | 厦门大学 | Simple and universal fish video image track tracking method |
| CN112492196A (en) * | 2020-10-29 | 2021-03-12 | 贝壳技术有限公司 | Live broadcast in-process anchor tracking method, device and system |
| CN112492196B (en) * | 2020-10-29 | 2022-01-07 | 贝壳技术有限公司 | Live broadcast in-process anchor tracking method, device and system |
| CN114419097A (en) * | 2021-12-30 | 2022-04-29 | 西安天和防务技术股份有限公司 | Target tracking method and device |
| CN115588154A (en) * | 2022-10-11 | 2023-01-10 | 湖北中医药大学 | System and method for recognizing and transcribing motion trail of acupuncture manipulation |
| CN115588154B (en) * | 2022-10-11 | 2024-06-07 | 湖北中医药大学 | Recognition transcription system and method for needling manipulation movement locus |
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