Recognition of two-person interactions using a hierarchical Bayesian network
IWVS '03 First ACM SIGMM international workshop on Video surveillance
Temporal spatio-velocity transform and its application to tracking and interaction
Computer Vision and Image Understanding - Special issue on event detection in video
Simultaneous tracking of multiple body parts of interacting persons
Computer Vision and Image Understanding
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Non Parametric Classification of Human Interaction
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Simultaneous tracking of multiple body parts of interacting persons
Computer Vision and Image Understanding
Human behavior analysis based on a new motion descriptor
IEEE Transactions on Circuits and Systems for Video Technology
Tracking and classifying of human motions with Gaussian process annealed particle filter
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Using Gaussian processes for human tracking and action classification
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
IEEE Transactions on Information Technology in Biomedicine
Simultaneous localization and tracking of persons in a cluttered scene with a single camera
SSIP'05 Proceedings of the 5th WSEAS international conference on Signal, speech and image processing
Tracking body parts of multiple people for multi-person multimodal interface
ICCV'05 Proceedings of the 2005 international conference on Computer Vision in Human-Computer Interaction
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Abstract: This paper presents a methodology for tracking persons and identifying two-person interactions in outdoor image sequences. By locating and tracking two persons over consecutive frames of monocular grayscale image sequences, we classify their interactions into several classes. Some of the interaction classes are: One person leaves another stationary person; two persons meet coming from different directions; and one stationary person starts following another walking person. We use side-view image sequences obtained by a fixed camera. In these image sequences the subjects are frequently occluded and move perpendicular to the direction of the camera. We present results on tracking of persons and their interactions.