The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Exploring the Space of a Human Action
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Efficient Visual Event Detection Using Volumetric Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
View Invariance for Human Action Recognition
International Journal of Computer Vision
The Function Space of an Activity
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Sharing Visual Features for Multiclass and Multiview Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Object Detection with Interleaved Categorization and Segmentation
International Journal of Computer Vision
Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words
International Journal of Computer Vision
Making action recognition robust to occlusions and viewpoint changes
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Learning dynamics for exemplar-based gesture recognition
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Expandable Data-Driven Graphical Modeling of Human Actions Based on Salient Postures
IEEE Transactions on Circuits and Systems for Video Technology
Sparse dictionary-based representation and recognition of action attributes
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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A unified tree-based framework for joint action localization, recognition and segmentation is proposed. An action is represented as a sequence of joint hog-flow descriptors extracted independently from each frame. During training, a set of action prototypes is first learned based on k-means clustering, and then a binary tree model is constructed from the set of action prototypes based on hierarchical k-means clustering. Each tree node is characterized by a hog-flow descriptor and a rejection threshold, and an initial action segmentation mask is defined for leaf nodes (corresponding to a prototype). During testing, an action is localized by mapping each test frame to its nearest neighbor prototype using a fast tree search method, followed by local search based tracking and global filtering based location refinement. An action is recognized by maximizing the sum of the joint probabilities of the action category and action prototype given an input sequence. An action pose from a test frame can be segmented by GrabCut algorithm using the initial segmentation mask from the matched leaf node as the user labeling. Our approach does not rely on background subtraction, and enables action localization and recognition in realistic and challenging conditions (such as crowded backgrounds). Experimental results show that our approach achieves start-of-art performances on the Weizmann dataset, CMU action dataset and UCF sports action dataset.