Robust industrial control: optimal design approach for polynomial systems
Robust industrial control: optimal design approach for polynomial systems
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
A tutorial on ν-support vector machines: Research Articles
Applied Stochastic Models in Business and Industry - Statistical Learning
International Journal of Computer Vision
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Head gesture recognition in intelligent interfaces: the role of context in improving recognition
Proceedings of the 11th international conference on Intelligent user interfaces
Estimating the Support of a High-Dimensional Distribution
Neural Computation
A ball tracking framework for broadcast soccer video
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Modeling people: vision-based understanding of a person's shape, appearance, movement, and behaviour
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Visual recognition of pointing gestures for human-robot interaction
Image and Vision Computing
Real-time human action recognition by luminance field trajectory analysis
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Representing pairwise spatial and temporal relations for action recognition
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Real-time human detection using relational depth similarity features
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
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We developed a new device-free user interface for TV viewing that uses a human gesture recognition technique. Although many motion recognition technologies have been reported, no man---machine interface that recognizes a large enough variety of gestures has been developed. The difficulty was the lack of spatial information that could be acquired from normal video sequences. We overcame the difficulty by using a time-of-flight camera and novel action recognition techniques. The main functions of this system are gesture recognition and posture measurement. The former is performed using the bag-of-features approach, which uses key-point trajectories as features. The use of 4-D spatiotemporal trajectory features is the main technical contribution of the proposed system. The latter is obtained through face detection and object tracking technology. The interface is useful because it does not require any contact-type devices. Several experiments proved the effectiveness of our proposed method and the usefulness of the system.