Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human motion analysis: a review
Computer Vision and Image Understanding
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
View-Invariant Representation and Recognition of Actions
International Journal of Computer Vision
3D Shape Histograms for Similarity Search and Classification in Spatial Databases
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
3-D model-based tracking of humans in action: a multi-view approach
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Invariant features for 3-D gesture recognition
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
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ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Inference of Human Postures by Classification of 3D Human Body Shape
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Pose-Based Clustering in Action Sequences
HLK '03 Proceedings of the First IEEE International Workshop on Higher-Level Knowledge in 3D Modeling and Motion Analysis
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Actions Sketch: A Novel Action Representation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
3D Shape Context Based Gesture Analysis Integrated with Tracking using Omni Video Array
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Diffusion Distance for Histogram Comparison
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Computational studies of human motion: part 1, tracking and motion synthesis
Foundations and Trends® in Computer Graphics and Vision
Markerless tracking of complex human motions from multiple views
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Free viewpoint action recognition using motion history volumes
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence
Searching for Complex Human Activities with No Visual Examples
International Journal of Computer Vision
Human action-recognition using mutual invariants
Computer Vision and Image Understanding
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Human action recognition using multiple views: a comparative perspective on recent developments
J-HGBU '11 Proceedings of the 2011 joint ACM workshop on Human gesture and behavior understanding
Recognizing activities in multiple views with fusion of frame judgments
Image and Vision Computing
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We address the problem of recognizing actions from arbitrary views for a multi-camera system. We argue that poses are important for understanding human actions and the strength of the pose representation affects the overall performance of the action recognition system. Based on this idea, we present a new view-independent representation for human poses. Assuming that the data is initially provided in the form of volumetric data, the volume of the human body is first divided into a sequence of horizontal layers, and then the intersections of the body segments with each layer are coded with enclosing circles. The circular features in all layers (i) the number of circles, (ii) the area of the outer circle, and (iii) the area of the inner circle are then used to generate a pose descriptor. The pose descriptors of all frames in an action sequence are further combined to generate corresponding motion descriptors. Action recognition is then performed with a simple nearest neighbor classifier. Experiments performed on the benchmark IXMAS multi-view dataset demonstrate that the performance of our method is comparable to the other methods in the literature.