A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
A general method for human activity recognition in video
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
Computer
Hidden Conditional Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words
International Journal of Computer Vision
Human Activity Recognition with Metric Learning
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Human motion recognition using support vector machines
Computer Vision and Image Understanding
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
Multi-view action recognition using local similarity random forests and sensor fusion
Pattern Recognition Letters
Robust human action recognition scheme based on high-level feature fusion
Multimedia Tools and Applications
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This paper presents two different classifier fusion algorithms applied in the domain of Human Action Recognition from video A set of cameras observes a person performing an action from a predefined set For each camera view a 2D descriptor is computed and a posterior on the performed activity is obtained using a soft classifier These posteriors are combined using voting and a bayesian network to obtain a single belief measure to use for the final decision on the performed action Experiments are conducted with different low level frame descriptors on the IXMAS dataset, achieving results comparable to state of the art 3D proposals, but only performing 2D processing.