3D Object in Clutter Recognition and Segmentation

by No License

3D Object in Clutter Recognition and Segmentation

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 repositorychef, t-rex, parasaurolophus, chicken, rhino from A. Mian object recognition datasetcat1, centaur1, david2, dog7, gorilla0, horse7, lioness13, victoria3, wolf2 from TOSCAs non-rigid worldface by Matteo Salaganesha from the Computer Vision lab in CaFoscarigun0026 from SHREC 2011 retrieval datasetA Scale Independent Selection Process for 3D Object Recognition in Cluttered scenes.Emanuele Rodolà, 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

Dataset Attributes

Label SVG
CategoriesMesh, Synthetic