Paper
25 October 2004 Face and facial parts tracking and its applications to nonverbal communication interface
Author Affiliations +
Proceedings Volume 5603, Machine Vision and its Optomechatronic Applications; (2004) https://doi.org/10.1117/12.580590
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States
Abstract
Since, at our laboratory, the basic configuration of the facial caricaturing system PICASSO has been constructed, it is strongly expected to get sufficient input image from a person who is naturally performing in front of the PICASSO camera system. From this viewpoint, we developed a face tracking PC system for capturing sufficient facial image especially in size by means of PTZ (Pan-Tilt-Zoom) camera collaborated with a fixed CCD camera. Irises are successfully recognized from the motion images captured from PTZ camera. These irises can be utilized to provide a key feature for realizing an automated facial recognizing system. In this system, a person performing naturally in pose and in facial expression within the scope of the fixed CCD camera can be stably tracked and the sufficient images in resolution of PTZ camera were successfully analyzed for iris recognition and facial parts extractions. This face tracking and face recognition system was characterized by a novel template replacement scheme among the successive image frames. Experimental results were also demonstrated in this paper. This system works well in a practical speed 6-9fps on a usual PC connected to these cameras.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Takuma Funahashi, Takayuki Fujiwara, Masafumi Tominaga, and Hiroyasu Koshimizu "Face and facial parts tracking and its applications to nonverbal communication interface", Proc. SPIE 5603, Machine Vision and its Optomechatronic Applications, (25 October 2004); https://doi.org/10.1117/12.580590
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KEYWORDS
Cameras

Facial recognition systems

Iris recognition

CCD cameras

Eye

Hough transforms

Machine vision

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