CN104504724B - A kind of moving body track and extraction algorithm not influenceed by barrier - Google Patents

A kind of moving body track and extraction algorithm not influenceed by barrier Download PDF

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CN104504724B
CN104504724B CN201510020446.5A CN201510020446A CN104504724B CN 104504724 B CN104504724 B CN 104504724B CN 201510020446 A CN201510020446 A CN 201510020446A CN 104504724 B CN104504724 B CN 104504724B
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characteristic point
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frame
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CN104504724A (en
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李竹
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HANGZHOU GUOCE MAP TECHNOLOGY Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/292—Multi-camera tracking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/254—Analysis of motion involving subtraction of images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence

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  • Computer Vision & Pattern Recognition (AREA)
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Abstract

The present invention designs a kind of Moving object extraction and track algorithm not influenceed by barrier, while the algorithm can also provide the Detailed motion information of target object various pieces while target object is followed the trail of.The algorithm extracts characteristic point to the continuous videos picture frame obtained by camera, and the characteristic point of acquisition is established into matching matrix, and the extraction of moving object and tracking are converted into an Assignment Problems, the matching relationship of characteristic point is obtained by solving an Assignment Problems, and realizes the extraction and tracking to mobile object.Because the algorithm handles multiple image frame simultaneously in matching, therefore when moving object is blocked by barrier, tracking is unaffected.

Description

A kind of moving body track and extraction algorithm not influenceed by barrier
Technical field
The present invention relates to the technical field of computer vision, more particularly to it is a kind of not by the moving object that barrier is influenceed with Track and extraction algorithm.
Background technology
The tracking of mobile object in the video that camera obtains is a focus in computer vision research field, Had broad application prospects in the systems such as robot vision, video monitoring.Conventional method such as background subtraction, continuous frame-to-frame differences Point-score can realize more good tracking effect in the case where camera is fixed, but in situation about being influenceed by barrier Under, the tracking of moving object would generally be interrupted.
The method for following the trail of mobile object that many researchers propose at present, such as optical flow method, based on SIFT feature Matching method, Mean-Shift methods and particle filter method can not solve the problems, such as to run into obstructing objects in tracking.Do not hindered It in application fields such as such as security protection, robot vision is essential to hinder moving body track that thing influences and extraction algorithm.
The content of the invention
It is an object of the present invention to provide a kind of moving body track and extraction algorithm not influenceed by barrier, the party Method can also provide the Detailed motion information of target object various pieces while target object is followed the trail of.Therefore, the algorithm is not Traditional method is only compared in the tracking of mobile object and outside more preferable effect, the Activity recognition of personage can also be applied to In field.
In order to realize foregoing invention purpose, the invention provides a kind of new movement matched simultaneously based on multiframe characteristic point Object tracking methods.When this method is first by the picture frame at the current time of the video image obtained by dollying head and before The picture frame at quarter extracts, and by the feature point extraction in image：
Assuming that the picture frame of current t is framet,
T frames before t are extracted simultaneously, and the T frames are framet-h, h=1 ... T },
To frametAnd framet-h, h=1 ... and T } extraction characteristic point, and protected in the characteristic point that each frame is extracted N number of characteristic point that stability is best is stayed, then the characteristic point sum being extracted is individual for N × (T+1).
Because the trajectory track problem of mobile object can be converted to of the various pieces in successive frame in mobile object With problem, therefore, by the matching result for trying to achieve each characteristic point of each characteristic point in present frame therewith in previous frame Obtain track of the mobile object in successive frame.
The matching result of the N × T of N number of characteristic point in present frame therewith in previous frame characteristic point is sought, N × N × T can be established Original beneficial matrix, matching result is motion track of each position of mobile object in successive frame.
The characteristic point of present frame therewith previous frame characteristic point matching when should meet following condition：
The cumulative total value of similarity between the characteristic point to match is maximum, i.e., the matching problem of 1 couple 1 can be considered as one The individual maximized optimization problem of global similarity, i.e. an Assignment Problems,.
When a new mobile object appears in picture frame picture first, the characteristic point of the mobile object may be therewith Any characteristic point of previous frame can not all be matched, and one kind as above-mentioned technical proposal is improved, former benefit of this programme to N × N × T Matrix is extended.
N × N × T original beneficial matrix is extended to N × (N × T+1).The element value of the expansion of beneficial matrix is default Threshold value.
Then the optimization matching of the matching problem of the characteristic point of previous frame is mathematically represented as the characteristic point of present frame therewith：
Minimize
s.t
pij={ 0,1 },
Wherein T be present frame before frame number, similarity { Curr (t)i, Prev (t-h)jIt is present frame characteristic point i Feature space space length between the characteristic point j of previous frame therewith, thresholdforcreating are default threshold value.
In actually calculating, similarity is calculated by the distance between feature histogram of two characteristic points.Therefore, it is global It is to minimize C that similarity, which maximizes actual,.The optimization matching of this 1 couple 1 can be considered as 1 Assignment Problems, and solve.
The characteristic point of present frame and threshold portion when matching, then this characteristic point is considered as belonging to new mobile object.
Previous frame in when belonging in the characteristic point of mobile object in the current frame without match point, previous frame in moving body quilt It is considered as and is blocked.The characteristic point being blocked within a certain period of time not again by the Feature Points Matching in current time picture frame, This feature point is considered as disappearing from picture.Again by current time picture frame after the mobile object being tracked is being blocked Feature Points Matching, this feature point is considered as the appearance again after blocking.
When the mobile object being tracked is being blocked, its position can do linear estimation by blocking front and rear position.
A kind of the advantage of the invention is that tracing algorithm that do not influenceed by barrier can be realized and interrupted.Hindered in object Hinder thing to realize lasting tracking when blocking, and position when being blocked can be extrapolated.This feature makes this method exist Relatively conventional method has more preferable applicability and practicality in terms of tracking object.In addition, technical scheme is due to can be with The various pieces of mobile object are tracked, therefore track characteristic can be provided for the Activity recognition of personage.
Brief description of the drawings
Fig. 1 is basic beneficial matrix schematic diagram.
Fig. 2 is the beneficial matrix schematic diagram after extension.
Fig. 3 is the final form for the matrix that heterochromia most has smallization.
Fig. 4 is the schematic diagram of shape and structure change constraint.
Embodiment
Characteristic point is extracted to each picture frame using SIFT algorithms in practical operation.And pass through the pixel around characteristic point Histograms of oriented gradients characteristic point is described.
In practical operation, after obtaining the feature histogram of each characteristic point, pass through Pasteur's distance 2 characteristic points of calculating The distance between feature histogram, i.e., the similarity of two characteristic points.The calculation formula of wherein Pasteur's distance is as follows：
Wherein p and q represents 2 normalized histograms of process respectively.
Assuming that retain the best N number of characteristic point of stability, the then feature being extracted in the characteristic point that each frame is extracted Point sum is individual for N × (T+1).
By be calculated all characteristic points of present frame and all characteristic points of previous frame between similarity after, can establish One basic beneficial matrix.The size of the beneficial matrix is N × N × T, as shown in Figure 1.The matching result of beneficial matrix is feature Motion track of the point in time space.
When a new mobile object appears in picture frame picture first, the characteristic point of the mobile object may be therewith Any characteristic point of previous frame can not all be matched, therefore N × N × T former beneficial matrix is extended.Former beneficial matrix is extended to N×(N×T+1).The element value of the expansion of beneficial matrix is default threshold value, as shown in Figure 2.The characteristic point of present frame with Threshold portion when matching, then this characteristic point is considered as belonging to new mobile object.
In actual match, previous frame in when belonging in the characteristic point of mobile object in the current frame without match point, before Moving body in frame is considered as being blocked.The characteristic point being blocked is not within a certain period of time again by current time picture frame Feature Points Matching, this feature point is considered as disappearing from picture.Worked as again after the mobile object being tracked is being blocked Feature Points Matching in preceding moment picture frame, this feature point are considered as the appearance again after blocking.
The matching example of the object that is actually blocked is provided in Fig. 3, the figure at characteristic point a and the t-3 moment in present frame t As the Feature Points Matching success in frame, then show that characteristic point a is blocked in t-2 the and t-3 moment by barrier, and in t Occur once again.
Fig. 4 provides the dead reckoning example of mobile object when being blocked by barrier, and the object of figure intermediate cam shape is in t+2 Moment is blocked, position 3 before being blocked according to it and the position 5 after being blocked can do linear reckoning, and it is when being blocked Position is 4.
It should be noted last that the above embodiments are merely illustrative of the technical solutions of the present invention and it is unrestricted.This area It will be appreciated by the skilled person that modified to technical scheme or equivalent substitution, such as the solution of optimization problem, Calculating of feature difference etc. all should be covered in claim of the invention without departure from the spirit and scope of technical solution of the present invention Among scope.

Claims (5)

  1. A kind of 1. moving body track and extraction algorithm not influenceed by barrier, it is characterised in that：
    S01：The picture frame of current t is designated as framet, and the T frames before t are designated as framet-h, h=1 ... T }, and Characteristic point is extracted respectively, and the feature point number of each frame is designated as N；
    S02：Then frame is calculatedtEach characteristic point and framet-h, the feature before h={ 1 ... T } each characteristic point is empty Between space length, establish a size be N × N × T original beneficial matrix；
    S03：Establish the expansion benefits matrix that a size is N × (T × N+1), including the original benefit square that T size is N × N The threshold matrix that battle array and a size are N × N；
    S04：Using the matching problem of beneficial matrix as a Solving Assignment Problem；
    S05：Whether it is new mobile object according to different matching result judging characteristic points, if the characteristic point and threshold of present frame The threshold value of value matrix matches, then this characteristic point is considered as belonging to new mobile object；
    S06：Whether disappeared according to continuous matching result judging characteristic point, when previous frame in belong in the characteristic point of mobile object In the current frame without can match point when, previous frame in mobile object be considered as being blocked or disappear；
    S07：Whether it is to occur again after blocking according to continuous matching result judging characteristic point；
    S08：Position of the characteristic point occurred again when blocking after being blocked according to the estimation of continuous matching result.
  2. A kind of 2. moving body track and extraction algorithm not influenceed by barrier according to claim 1, it is characterized in that N × (T × N+1) beneficial matrix includes the original beneficial matrix that T size is N × N and the threshold value square that a size is N × N Battle array.
  3. 3. a kind of moving body track and extraction algorithm not influenceed by barrier according to claim 1, it is characterized in that Its optimization matching is mathematically represented as：
    Minimize
    <mrow> <mi>C</mi> <mo>=</mo> <munderover> <mi>&amp;Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <munderover> <mi>&amp;Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>N</mi> <mo>&amp;times;</mo> <mrow> <mo>(</mo> <mi>T</mi> <mo>&amp;times;</mo> <mi>N</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </munderover> <msub> <mi>p</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <msub> <mi>c</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> </mrow>
    s.t
    <mrow> <munderover> <mi>&amp;Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>N</mi> <mo>&amp;times;</mo> <mrow> <mo>(</mo> <mi>T</mi> <mo>&amp;times;</mo> <mi>N</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </munderover> <msub> <mi>p</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>N</mi> <mo>}</mo> <mo>,</mo> </mrow>
    <mrow> <munderover> <mi>&amp;Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msub> <mi>p</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>&amp;le;</mo> <mn>1</mn> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>N</mi> <mo>&amp;times;</mo> <mrow> <mo>(</mo> <mi>T</mi> <mo>&amp;times;</mo> <mi>N</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>}</mo> <mo>,</mo> </mrow>
    pij={ 0,1 },
    <mrow> <mi>c</mi> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mi>s</mi> <mi>i</mi> <mi>m</mi> <mi>i</mi> <mi>l</mi> <mi>a</mi> <mi>r</mi> <mi>i</mi> <mi>t</mi> <mi>y</mi> <mo>{</mo> <mi>C</mi> <mi>u</mi> <mi>r</mi> <mi>r</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mi>i</mi> <mo>,</mo> <mi>Pr</mi> <mi>e</mi> <mi>v</mi> <msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>h</mi> <mo>)</mo> </mrow> <mi>j</mi> </msub> <mo>}</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>h</mi> <mo>=</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>T</mi> <mo>}</mo> <mo>,</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>i</mi> <mo>=</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mn>...</mn> <mi>N</mi> <mo>}</mo> <mo>,</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>j</mi> <mo>=</mo> <mo>{</mo> <mrow> <mo>(</mo> <mi>h</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>&amp;times;</mo> <mi>N</mi> <mo>+</mo> <mn>1</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>h</mi> <mo>&amp;times;</mo> <mi>N</mi> <mo>}</mo> <mo>,</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>T</mi> <mi>h</mi> <mi>r</mi> <mi>e</mi> <mi>s</mi> <mi>h</mi> <mi>o</mi> <mi>l</mi> <mi>d</mi> <mi> </mi> <mi>f</mi> <mi>o</mi> <mi>r</mi> <mi> </mi> <mi>c</mi> <mi>r</mi> <mi>e</mi> <mi>a</mi> <mi>t</mi> <mi>i</mi> <mi>n</mi> <mi>g</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>i</mi> <mo>=</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mn>...</mn> <mi>N</mi> <mo>}</mo> <mo>,</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>j</mi> <mo>=</mo> <mo>{</mo> <mrow> <mo>(</mo> <mi>T</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>&amp;times;</mo> <mi>N</mi> <mo>+</mo> <mn>1</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mrow> <mo>(</mo> <mi>T</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>&amp;times;</mo> <mi>N</mi> <mo>}</mo> <mo>.</mo> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
    Wherein T be present frame before frame number, similarity { Curr (t)i, Prev (t-h)jFor present frame characteristic point i therewith Feature space space length between the characteristic point j of previous frame, threshold for creating are default threshold value.
  4. 4. a kind of moving body track and extraction algorithm not influenceed by barrier according to claim 3, it is characterized in that When the mobile object being tracked is being blocked, its position can do linear estimation by blocking front and rear position.
  5. 5. a kind of moving body track and extraction algorithm not influenceed by barrier according to claim 1, it is characterized in that When the mobile object being tracked is being blocked, the tracking to object will not be interrupted.
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CN106096508B (en) * 2016-05-30 2019-09-13 无锡天脉聚源传媒科技有限公司 The method and device that target is covered is determined in a kind of image
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