Recognition of human behavior by space-time silhouette characterization
Pattern Recognition Letters
Microcontroller and sensors based gesture vocalizer
ISPRA'08 Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation
International Journal of Computer Vision
Recognizing events with temporal random forests
Proceedings of the 2009 international conference on Multimodal interfaces
Recognizing Gestures for Virtual and Real World Interaction
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Human silhouette extraction method using region based background subtraction
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Multiple people gesture recognition for human-robot interaction
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Real-time vision based gesture recognition for human-robot interaction
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
MAPACo-training: a novel online learning algorithm of behavior models
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
A shared parameter model for gesture and sub-gesture analysis
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
Recovery of surgical workflow without explicit models
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Accurate foreground extraction using graph cut with trimap estimation
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Vision-based arm gesture recognition for a long-range human---robot interaction
The Journal of Supercomputing
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A novel method is introduced to recognize and estimate the scale of time-varying human gestures. It exploits the changes in contours along spatio-temporal directions. Each contour is first parameterized as a 2D function of radius vs. cumulative contour length, and a 3D surface is composed from a sequence of such functions. In a two-phase recognition process, Dynamic TimeWarping is employed to rule out significantly different gesture models, and then Mutual Information (MI) is applied for matching the remaining models. The system has been tested on 8 gestures performed by 5 subjects with varied time scales. The two-phase process is compared against exhaustively testing three similarity measures based upon MI, Correlation, and Nonparametric Kernel Density Estimation. Experimental results demonstrate that the exhaustive application of MI is the most robust with a recognition rate of 90.6%, however, the two-phase approach is much more computationally efficient with a comparable recognition rate of 90.0%.