Illumination color covariant locale-based visual object retrieval
Illumination color covariant locale-based visual object retrieval
复制标题
基于照明颜色协变区域设置的视觉对象检索
DOI：
10.1016/s0031-3203(01)00163-7
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Z. Tauber
中科院分区：
文献类型：
--
作者：
M. S. Drew;Ze;Z. Tauber
Search by object model — finding an object inside a target image — is a desirable and yet difficult mechanism for querying multi-media data. An added difficulty is that objects can be photographed under different lighting conditions. While human vision has color constancy, an invariant processing, presumably, here we seek only covariant processing and look to recover such lighting change. Making use of feature-consistent locales in an image we develop a scene partition by localization, rather than by image segmentation. A diagonal model for illumination change and a voting scheme in chromaticity space provide a candidate set of lighting change coefficients for covariant image transformation. For each pair of coefficients, Elastic Correlation, a form of correlation of locale colors, is performed along with a least squares minimization for pose estimation. Since the rotation, scale and translation parameters are thus estimated, we can apply an efficient process of texture support and shape verification. Tests on an image and video database of about 1500 images show an average recall and precision of over 70%.
