Description

The dataset is composed of 150 synthetic scenes, captured with a (perspective) virtual camera, and each scene contains 3 to 5 objects. The model set is composed of 20 different objects, taken from different sources and then processed in order to obtain comparably smooth surfaces of almost uniform 100-350k triangles with an average resolution of 1.0. In particular, the model set contains processed versions of: armadillo, bunny, dragon from the Stanford 3D scanning repository chef, t-rex, parasaurolophus, chicken, rhino from A. Mian object recognition dataset cat1, centaur1, david2, dog7, gorilla0, horse7, lioness13, victoria3, wolf2 from TOSCAs non-rigid world face by Matteo Sala ganesha from the Computer Vision lab in CaFoscari gun0026 from SHREC 2011 retrieval dataset A Scale Independent Selection Process for 3D Object Recognition in Cluttered scenes. Emanuele Rodol, Andrea Albarelli, Filippo Bergamasco, and Andrea Torsello. International Journal of Computer Vision (IJCV) - Special Issue on 3D Imaging, Processing and Modeling Techniques. March 2013, Vol.102 Issue 1, pp 129-145

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