H. Dutagaci, A. Godil, P. Daras, A. Axenopoulos, G. Litos, S. Manolopoulou, K. Goto, T. Yanagimachi, Y. Kurita, S. Kawamura, T. Furuya, and R. Ohbuchi
In this paper we present the results of the 3D Shape Retrieval Contest 2011 (SHREC'11) track on generic shape retrieval. The aim of this track is to evaluate the performance of 3D shape retrieval algorithms that can operate on arbitrary 3D models. The benchmark dataset consists of 1000 3D objects classified in 50 categories. The 3D models are mainly classified based on visual shape similarity and each class has equal number of models to reduce the possible bias in evaluation results. Two groups have participated in the track with six methods in total.
Categories and Subject Descriptors (according to ACM CCS): I.5.4 [Pattern Recognition]: Applications-Computer vision; H.3.3 [Computer Graphics]: Information Systems-Information Search and Retrieval