Design of a real-time gesture recognition system: high performance through algorithms and software

The embedded systems group at Princeton University in New Jersey has developed, as an example of smart cameras, a gesture recognition system that can build a complete model of the torso and recognize gestures at 30 frames/s. Designing a real-time gesture recognition system is a complex task that involves many issues such as algorithm design, processing speed, system architecture, and video interface. In this article, the authors describe a method to manage the complexity by decomposing the entire process into different design and implementation phases.

[1]  T. Wiangtong,et al.  Hardware/software codesign: a systematic approach targeting data-intensive applications , 2005, IEEE Signal Processing Magazine.

[2]  Randy Allen.  Compiling High-Level Languages to DSPs , 2005 .

[3]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[4]  Marco Platzner,et al.  Hardware-Software Codesign , 1997, IEEE Des. Test Comput..

[5]  William H. Press,et al.  Book-Review - Numerical Recipes in Pascal - the Art of Scientific Computing , 1989 .

[6]  R. Allen,et al.  Compiling high-level languages to DSPs: automating the implementation path , 2005, IEEE Signal Processing Magazine.

[7]  Lothar Thiele,et al.  Performance Analysis of Multiprocessor DSPs , 2005 .

[8]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[9]  L. Thiele,et al.  Performance analysis of multiprocessor DSPs: a stream-oriented component model , 2005, IEEE Signal Processing Magazine.

[10]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[11]  M.F. Jacome,et al.  Energy-delay efficient data memory subsystems: suitable for embedded media "processing" , 2005, IEEE Signal Processing Magazine.

[12]  Larry S. Davis,et al.  W/sup 4/: Who? When? Where? What? A real time system for detecting and tracking people , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[13]  J.B. Burns,et al.  View Variation of Point-Set and Line-Segment Features , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Alex Pentland,et al.  Pfinder: Real-Time Tracking of the Human Body , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Larry S. Davis,et al.  W4S : A real-time system for detecting and tracking people in 2 D , 1998, eccv 1998.

[16]  Margarida F. Jacome,et al.  Energy-Delay Efficient Data Memory Subsystems , 2005 .

[17]  Walter F. Bischof,et al.  Machine Learning and Image Interpretation , 1997, Advances in Computer Vision and Machine Intelligence.