Sigal Berman, Yael Edan, Helman Stern
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev
The objective of the research was to developed a hand–gesture based remote control system for home-entertainment scenarios. With the course of the research we have examined various input sensors, and developed motion tracking and classification algorithms. Additionally we have developed a signature-gesture based user identification system.
>> S. Berman, H. Stern, 2012. Sensors for Gesture Recognition Systems, IEEE Transactions on Systems, Man, and Cybernetics-Part C, 42(3):277-290.
>> D. Frolova, H. Stern, S. Berman, 2012. Most Probable Longest Common Subsequence for Recognition of Gesture Character Input, IEEE Transactions on Systems Man and Cybernetics, part B, 43(3): 871-880.
>> H. Stern, M. Shmueli, S. Berman, 2013. Most Discriminating Segment - Longest Common Subsequence (MDSLCS) Algorithm for Dynamic Hand Gesture Classification, Pattern Recognition Letters (Special issue on 'Smart Approaches for Human Action Recognition’), 34: 1980-1989.
>> O. Mendels, H. Stern, S. Berman, 2014. Biometric Identification by Hand Motion Signature, IEEE Transactions on Systems Man and Cybernetic: Systems, In Print.
Funding: Deutsche Telekom AG