Performance of Eye Detection by Genetic Algorithms

T. Akashi, Y. Wakasa, and K. Tanaka (Japan)


Computer Vision, Genetic Algorithms, Human Interface, and Eye detection


We propose a high-speed size and orientation invariant eye detection in an active scene. As part of the objectives, we also try to acquire numerical parameters to represent the eye, for example, position, scaling and rotation angle. The information is useful for many applications, where high performance is required, such as eye gaze detection or esti mation for robot perception and mobile devices interfaces. The difficulty in eye tracking is mainly due to motion of the human head and the active scene by free camera mo tion. The proposed system is based on template match ing using genetic algorithms (GAs). The generality of the proposed method is provided by the artificial iris template used. Various geometric changes of iris can be supported by GAs. In this paper, eye detection method with GAs is proposed. Moreover the effectiveness is evaluated by com parison with a representative method. These results indi cate that the detection accuracy of the both methods is same (about 90% ) in the simple situation. On the other hand, the proposed method is more robust to the complex situation than the a representative method. The processing time is fast enough for real-time processing.

Important Links:

Go Back