Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems
Theoretical Computer Science
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminant Analysis of Principal Components for Face Recognition
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Real-Time Context-Based Gesture Recognition Using HMM and Automaton
RATFG-RTS '99 Proceedings of the International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Hidden Markov Model Based Continuous Online Gesture Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Space-Time Behavior Based Correlation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
International Journal of Computer Vision
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
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
Behavior recognition via sparse spatio-temporal features
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
Journal of Cognitive Neuroscience
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Histogram of oriented rectangles: A new pose descriptor for human action recognition
Image and Vision Computing
Human Action Recognition in Videos Using Kinematic Features and Multiple Instance Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey on vision-based human action recognition
Image and Vision Computing
Hierarchical Human Action Recognition by Normalized-Polar Histogram
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
A survey of vision-based methods for action representation, segmentation and recognition
Computer Vision and Image Understanding
Action recognition from a distributed representation of pose and appearance
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Real-time human pose recognition in parts from single depth images
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Fusion of human posture features for continuous action recognition
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
A line based pose representation for human action recognition
Image Communication
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Online human gesture recognition from motion data streams
Proceedings of the 21st ACM international conference on Multimedia
Ongoing human action recognition with motion capture
Pattern Recognition
Proceedings of the 10th European Conference on Visual Media Production
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This paper presents a novel and efficient framework for human action recognition based on modeling the motion of human body-parts. Intuitively, a collective understanding of human body-part movements can lead to better understanding and representation of any human action. In this paper, we propose a generative representation of the motion of human body-parts to learn and classify human actions. The proposed representation combines the advantages of both local and global representations, encoding the relevant motion information as well as being robust to local appearance changes. Our work is motivated by the pictorial structures model and the framework of sparse representations for recognition. Human body-part movements are represented efficiently through quantization in the polar space. The key discrimination within each action is efficiently encoded by sparse representation for classification. The proposed framework is evaluated on both the KTH and the UCF Sport action datasets and results compared against several state-of-the-art methods.