Host: Japan SOciety for Fuzzy Theory and intelligent informatics
Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"
This paper proposes the use of gradient orientation information, instead of traditional image information such as intensities and gradient vectors, for estimating motion in image sequences. Gradient orientation information may be exploited with unit gradient vectors that are invariant to image intensities to a great extent. By replacing image intensities or gradient vectors with the unit gradient vector, the robustness of traditional motion estimation techniques to changes in lighting conditions can be significantly improved. We describe two motion estimation techniques based on gradient orientation information. The proposed techniques work robustly regardless of varying image intensities. In addition, they show an improved tolerance to low image contrast, and the so-called aperture problem that makes existing motion estimation techniques ineffective.
