1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97)
Object recognition using invariant profiles
Puerto Rico
June 17-June 19
ISBN: 0-8186-7822-4
D. Slater, Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
G. Healey, Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
We derive a sensitivity analysis for moment invariants of multidimensional distributions. These invariants have many uses in computational systems and have recently been used for illumination-invariant recognition in color images. In this context, the sensitivity analysis predicts the response of moment invariants to partial occlusion. Using the results of the sensitivity analysis, we develop a novel surface representation called the invariant profile which captures color distribution and spatial information while remaining invariant to the spectral content of the scene illumination. Unlike previous representations, the recognition of invariant profiles does not require illumination correction. We demonstrate the sensitivity analysis and the use of invariant profiles for recognition with a set of experiments on color images.
Index Terms:
object recognition; object recognition; invariant profiles; sensitivity analysis; multidimensional distributions; illumination-invariant recognition; color images; surface representation
Citation:
D. Slater, G. Healey, "Object recognition using invariant profiles," cvpr, pp.827, 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), 1997