@inproceedings{ Sethi2011a,
  abstract = {This paper concentrates on the problem of modelling and recognition of complex behaviours involving multi-object interactions in video. We use motion patterns of individual objects to construct models which characterize pairs by cor- relating them in phase space. These models of complex in- teractions allow for: recognition of group activities, which occur when individual people or objects start interacting as a single entity; detection of transitions from individu- als to groups to crowds; and the interactions of individu- als with groups, as well as the interactions of groups with other groups. We establish a general formalism by exam- ining activities using relative distances and analyse multi- object interactions directly via the Phase Space Algorithm. Finally, we calculate a scale-invariant Group Transition Ratio to quantify formation and dispersal of both groups and crowds. Our input is solely the position information of individuals, which we get using a person tracker, optical flow, and Lagrangian particle dynamics. We demonstrate the uses of this model for recognition of complex activi- ties on the standard CAVIAR, VIVID, and UCR Videoweb datasets.},
  author = {Sethi, Ricky J and Roy-Chowdhury, Amit K},
  booktitle = {ICCV VECTaR},
  file = {:C$\backslash$:/Users/rjs/Documents/Mendeley Desktop/Sethi, Roy-Chowdhury/ICCV VECTaR/Sethi, Roy-Chowdhury_2011_Individuals, Groups, and Crowds Modelling Complex, Multi-Object Behaviour in Phase Space.pdf:pdf},
  title = {{Individuals, Groups, and Crowds: Modelling Complex, Multi-Object Behaviour in Phase Space}},
  year = {2011}
}

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We use motion patterns of individual objects to construct models which characterize pairs by cor- relating them in phase space. These models of complex in- teractions allow for: recognition of group activities, which occur when individual people or objects start interacting as a single entity; detection of transitions from individu- als to groups to crowds; and the interactions of individu- als with groups, as well as the interactions of groups with other groups. We establish a general formalism by exam- ining activities using relative distances and analyse multi- object interactions directly via the Phase Space Algorithm. Finally, we calculate a scale-invariant Group Transition Ratio to quantify formation and dispersal of both groups and crowds. Our input is solely the position information of individuals, which we get using a person tracker, optical flow, and Lagrangian particle dynamics. We demonstrate the uses of this model for recognition of complex activi- ties on the standard CAVIAR, VIVID, and UCR Videoweb datasets. -->\n<!-- </div> -->\n<!-- -->\n\n</div>\n","downloads":0,"urls":{},"abstract":"This paper concentrates on the problem of modelling and recognition of complex behaviours involving multi-object interactions in video. We use motion patterns of individual objects to construct models which characterize pairs by cor- relating them in phase space. These models of complex in- teractions allow for: recognition of group activities, which occur when individual people or objects start interacting as a single entity; detection of transitions from individu- als to groups to crowds; and the interactions of individu- als with groups, as well as the interactions of groups with other groups. We establish a general formalism by exam- ining activities using relative distances and analyse multi- object interactions directly via the Phase Space Algorithm. Finally, we calculate a scale-invariant Group Transition Ratio to quantify formation and dispersal of both groups and crowds. Our input is solely the position information of individuals, which we get using a person tracker, optical flow, and Lagrangian particle dynamics. We demonstrate the uses of this model for recognition of complex activi- ties on the standard CAVIAR, VIVID, and UCR Videoweb datasets.","author":["Sethi","J, Ricky","Roy-Chowdhury","K, Amit"],"author_short":["Sethi","J, R.","Roy-Chowdhury","K, A."],"bibtex":"@inproceedings{ Sethi2011a,\n abstract = {This paper concentrates on the problem of modelling and recognition of complex behaviours involving multi-object interactions in video. We use motion patterns of individual objects to construct models which characterize pairs by cor- relating them in phase space. These models of complex in- teractions allow for: recognition of group activities, which occur when individual people or objects start interacting as a single entity; detection of transitions from individu- als to groups to crowds; and the interactions of individu- als with groups, as well as the interactions of groups with other groups. We establish a general formalism by exam- ining activities using relative distances and analyse multi- object interactions directly via the Phase Space Algorithm. Finally, we calculate a scale-invariant Group Transition Ratio to quantify formation and dispersal of both groups and crowds. Our input is solely the position information of individuals, which we get using a person tracker, optical flow, and Lagrangian particle dynamics. We demonstrate the uses of this model for recognition of complex activi- ties on the standard CAVIAR, VIVID, and UCR Videoweb datasets.},\n author = {Sethi, Ricky J and Roy-Chowdhury, Amit K},\n booktitle = {ICCV VECTaR},\n file = {:C$\\backslash$:/Users/rjs/Documents/Mendeley Desktop/Sethi, Roy-Chowdhury/ICCV VECTaR/Sethi, Roy-Chowdhury_2011_Individuals, Groups, and Crowds Modelling Complex, Multi-Object Behaviour in Phase Space.pdf:pdf},\n title = {{Individuals, Groups, and Crowds: Modelling Complex, Multi-Object Behaviour in Phase Space}},\n year = {2011}\n}","bibtype":"inproceedings","booktitle":"ICCV VECTaR","file":":C$\\backslash$:/Users/rjs/Documents/Mendeley Desktop/Sethi, Roy-Chowdhury/ICCV VECTaR/Sethi, Roy-Chowdhury_2011_Individuals, Groups, and Crowds Modelling Complex, Multi-Object Behaviour in Phase Space.pdf:pdf","id":"Sethi2011a","key":"Sethi2011a","title":"Individuals, Groups, and Crowds: Modelling Complex, Multi-Object Behaviour in Phase Space","type":"inproceedings","year":"2011","role":"author","bibbaseid":"-j--k-individualsgroupsandcrowdsmodellingcomplexmultiobjectbehaviourinphasespace-2011"},"bibtype":"inproceedings","biburl":"http://www.sethi.org/papers/my_papers.bib","downloads":0,"title":"Individuals, Groups, and Crowds: Modelling Complex, Multi-Object Behaviour in Phase Space","year":2011,"dataSources":["tdeDoF6pkYnHWtGXW"]}