Laura Leal-Taix´e, Gerard Pons-Moll and Bodo Rosenhahn ICCV2011
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Transcript of Laura Leal-Taix´e, Gerard Pons-Moll and Bodo Rosenhahn ICCV2011
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Everybody needs somebody: Modeling social and grouping behavior on a linearprogramming multiple people trackerLaura Leal-Taixe, Gerard Pons-Moll and Bodo RosenhahnICCV2011
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OutlineGoalMultiple people trackingModeling social behaviorExperimental resultsConclusion
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GoalPeople detection is not always correct.It is important to merge the detection results into right trajectoies.
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Multiple people trackingdivided in two stepsobject detectiondata associationform complete trajectoriesBuild a graph with the nodes pedestrian detectionsThe matching problem is equivalent to minimum-cost network flow problem
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Multiple people tracking ,trajectory of kFind the that best explains the detection. 4
P(oi|T) is the likelihood.
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Multiple people tracking trajectory Tk have following dependenciesConstant velocity assumption find oi depends on oi-1,oi-2Grouping behavior Avoidance term
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Multiple people tracking
Represent by Markov chain:
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Multiple people tracking
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Multiple people trackingCombine (1),(2),(3)
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Multiple people trackingThree kinds of edges:Link edgesDetection edgesEntrance and exit edges
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Multiple people trackingLink edgesThe edges (ei, bj) connect the end nodes ei with the beginning nodes bj in following frames,with cost Ci,j and flag fi,jFlag =1 if oi and oj belong to Tk,and fFmax111
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Multiple people trackingDetection edgesThe edges (bi, ei) connect the beginning node bi and end node ei, with cost Ci and flag fi
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Modeling social behaviorIf a pedestrian doesnt meet any obstacles, he will naturally follow a straight line.But the pedestrian will have some social behavior.Add Social Force Model (SFM)and Group behavior(GR) into the problem.
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Modeling social behaviorSocial forces have three main terms:The desire to maintain certain speedThe desire to keep away from othersThe desire to reach a destinationWe focus on first two!
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Modeling social behavior
Constant velocity assumpionWhen a person walk at a speed V at time tWe assume he will have speed V at time t+t
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Modeling social behaviorAvoidance term
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Modeling social behaviorFrom the training sequence in [22] , we learn the probabilty of Pg and Pi
[22] S. Pellegrini, A. Ess, K. Schindler, and L. van Gool. Youll never walk alone: modeling social behavior for multi-target tracking. ICCV, 2009. 1, 2, 5, 7
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Experimental resultsBlue=>DISTGreed=>with SDMRed=>SFM+GR
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Experimental results
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Experimental resultsTo show the importance of social behavior and the robustness of our algorithm at low frame rates, we track at 2.5fps (taking one every tenth frame).
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Experimental resultsDA (detection accuracy)TA (tracking accuracy)DP (detection precision)TP (tracking precision)
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Experimental results
[28]use network flow[22]use social behavior[27] use social and grouping
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Experimental results
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ConclusionIt is important to have social and group relation on tracking.This paper outperform on low fps than others and have high accuracies on miss detections,false alarms and noise.