Tracking and recognizing actions of multiple hockey players using the boosted particle filter
Image and Vision Computing
Multi-view Player Action Recognition in Soccer Games
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
Tracking HoG Descriptors for Gesture Recognition
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
A survey on vision-based human action recognition
Image and Vision Computing
Behavior histograms for action recognition and human detection
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
A parallel histogram-based particle filter for object tracking on SIMD-based smart cameras
Computer Vision and Image Understanding
Recognizing human action from a far field of view
WMVC'09 Proceedings of the 2009 international conference on Motion and video computing
An incremental PCA-HOG descriptor for robust visual hand tracking
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Adaptive multi-cue tracking by online appearance learning
Neurocomputing
kpose: a new representation for action recognition
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
HOG-based descriptors on rotation invariant human detection
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
Topic based pose relevance learning in dance archives
Proceedings of the 21st ACM international conference on Information and knowledge management
(MP)2T: multiple people multiple parts tracker
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Human focused action localization in video
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
Discriminative fusion of shape and appearance features for human pose estimation
Pattern Recognition
Exploring trace transform for robust human action recognition
Pattern Recognition
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This paper presents a template-based algorithm to track and recognize athlete's actions in an integrated system using only visual information. Conventional template-based action recognition systems usually consider action recognition and tracking as two independent problems, and solve them separately. In contrast, our algorithm emphasizes that tracking and action recognition can be tightly coupled into a single framework, where tracking assists action recognition and vise versa. Moreover, this paper proposes to represent the athletes by the PCA-HOG descriptor, which can be computed by first transforming the athletes to the grids of Histograms of Oriented Gradient (HOG) descriptor and then project it to a linear subspace by Principal Component Analysis (PCA). The exploitation of the PCA-HOG descriptor not only helps the tracker to be robust under illumination, pose, and view-point changes, but also implicitly centers the figure in the tracking region, which makes action recognition possible. Empirical results in hockey and soccer sequences show the effectiveness of this algorithm.