Signal Processing - Video segmentation for content-based processing manipulation
A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Large-Scale Event Detection Using Semi-Hidden Markov Models
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Statistical Video Content Recognition Method Using Invariant Features on Object Trajectories
IEEE Transactions on Circuits and Systems for Video Technology
Multifeature Object Trajectory Clustering for Video Analysis
IEEE Transactions on Circuits and Systems for Video Technology
Event Detection Using Trajectory Clustering and 4-D Histograms
IEEE Transactions on Circuits and Systems for Video Technology
Trajectory-Based Anomalous Event Detection
IEEE Transactions on Circuits and Systems for Video Technology
Team activity recognition in sports
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
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This paper presents a content-based approach for understanding handball videos. Tracked players are characterized by their 2D trajectories in the court plane. The trajectories and their interactions are used to model visual semantics, i.e., the observed activity phases. To this end, hierarchical parallel semi-Markov models (HPaSMMs) are computed in order to take into account the temporal causalities of object motions. Players motions are characterized using velocity informations while their interactions are described by the distances between trajectories. We have evaluated our method on real video sequences, and have favorably compared with another method, i.e., hierarchical parallel hidden Markov models (HPaHMMs).