Title :
Distinctive parts for shape classification
Author :
Li, Chunyuan ; You, Xinge ; Ben Hamza, A. ; Zeng, Wu ; Zhou, Long
Author_Institution :
Dept. of Electron. & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
Shape is an important cue for object recognition, While previous research on shape classification uses all parts of a feature set (e.g. contour segments, skeleton paths), we define distinctive parts that tell an object from objects of a different type. Our approach to analyze distinctive part is based on performing a shape-based search using each part as a query into a database. Distinctive parts of a shape are consistent with objects of the same type and different from objects of other types. Experimental results demonstrate that the concept agrees with human common sense, and show the effectiveness and efficiency of our method for shape classification as well.
Keywords :
image classification; object recognition; shape recognition; distinctive parts classification; object recognition; shape based search; shape classification; Accuracy; Classification algorithms; Computational modeling; Distinctive parts; contour segment; shape classification; skeleton path;
Conference_Titel :
Wavelet Analysis and Pattern Recognition (ICWAPR), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4577-0283-9
DOI :
10.1109/ICWAPR.2011.6014505