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IEEE Transactions on Pattern Analysis and Machine Intelligence
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
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
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hand gesture recognition with a novel IR time-of-flight range camera: a pilot study
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Action and gait recognition from recovered 3-D human joints
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
A survey of vision-based methods for action representation, segmentation and recognition
Computer Vision and Image Understanding
Video-rate capture of dynamic face shape and appearance
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Hand gesture recognition using depth data
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Real-time classification of dance gestures from skeleton animation
SCA '11 Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Recognition and segmentation of 3-d human action using HMM and multi-class adaboost
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Expandable Data-Driven Graphical Modeling of Human Actions Based on Salient Postures
IEEE Transactions on Circuits and Systems for Video Technology
Recognizing actions using depth motion maps-based histograms of oriented gradients
Proceedings of the 20th ACM international conference on Multimedia
Real-Time Gesture Recognition from Depth Data through Key Poses Learning and Decision Forests
SIBGRAPI '12 Proceedings of the 2012 25th SIBGRAPI Conference on Graphics, Patterns and Images
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We present a new visual representation for 3D action recognition from sequences of depth maps. In this new representation, space and time axes are divided into multiple segments to define a 4D grid for each depth map sequences. Each cell in the grid is associated with an occupancy value which is a function of the number of space-time points falling into this cell. The occupancy values of all the cells form a high dimensional feature vector, called Space-Time Occupancy Pattern (STOP). We then perform dimensionality reduction to obtain lower-dimensional feature vectors. The advantage of STOP is that it preserves spatial and temporal contextual information between space and time cells while being flexible enough to accommodate intra-action variations. Furthermore, we combine depth maps with skeletons in order to obtain view invariance and present an automatic segmentation and time alignment method for on-line recognition of depth sequences. Our visual representation is validated with experiments on a public 3D human action dataset.