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
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Use of the zero norm with linear models and kernel methods
The Journal of Machine Learning Research
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Integral Histogram: A Fast Way To Extract Histograms in Cartesian Spaces
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
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
International Journal of Computer Vision
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Statistical Analysis of Dynamic Actions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Behavior recognition via sparse spatio-temporal features
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
A 3-dimensional sift descriptor and its application to action recognition
Proceedings of the 15th international conference on Multimedia
Image Feature Extraction Using Gradient Local Auto-Correlations
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
An Efficient Dense and Scale-Invariant Spatio-Temporal Interest Point Detector
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Human Action Recognition by Semilatent Topic Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing human actions by fusing spatio-temporal appearance and motion descriptors
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Efficient optimization for low-rank integrated bilinear classifiers
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
A tensor motion descriptor based on histograms of gradients and optical flow
Pattern Recognition Letters
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In this paper, we propose a motion recognition scheme based on a novel method of motion feature extraction. The feature extraction method utilizes auto-correlations of space-time gradients of three-dimensional motion shape in a video sequence. The method effectively exploits the local relationships of the gradients corresponding to the space-time geometric characteristics of the motion. For recognizing motions, we apply the framework of bag-of-frame-features, which, in contrast to the standard bag-of-features framework, enables the motion characteristics to be captured sufficiently and the motions to be quickly recognized. In experiments on various datasets for motion recognition, the proposed method exhibits favorable performances as compared to the other methods, and faster computational time even than real time.