language: en

A Chromaticity Space for Specularity, Illumination Color- and Illumination Pose-Invariant 3-D Object Recognition

Daniel Berwick and Sang Wook Lee
(dberwick@umich.edu and swlee@umich.edu)
Dept. of Electrical Enginnering and Computer Science University of Michigan
Ann Arbor, MI 48104

Abstract Most of the recent color recognition/indexing approaches concentrate on establishing invariance to illumination color to improve the utility of color recognition. However, other effects caused by illumination pose and specularity on three-dimensional object surfaces have not received notable attention. We present a chromaticity recognition method that discounts the effects of illumination pose, illumination color and specularity. It utilizes a chromaticity space based on log-ratio of sensor responses for illumination pose and color invariance. A model-based specularity detection/rejection algorithm can be used to improve the chromaticity recognition and illumination estimation for objects including specular reflections.