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Robust Object Categorization and Segmentation Motivated by Visual Contexts in the Human Visual System
2010
EURASIP Journal on Advances in Signal Processing
Categorizing visual elements is fundamentally important for autonomous mobile robots to get intelligence such as novel object learning and topological place recognition. The main difficulties of visual categorization are two folds: large internal and external variations caused by surface markings and background clutters, respectively. In this paper, we present a new object categorization method robust to surface markings and background clutters. Biologically motivated codebook selection method
doi:10.1155/2011/101428
fatcat:jkh6t2ymgne6hkad6ptto4jgzu