Brkic, KarlaAldomà, AitorVincze, MarkusSegvic, SinisaKalafatic, ZoranBenjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkamp2014-12-152014-12-152014978-3-905674-58-31997-0463http://dx.doi.org/10.2312/3dor.20141050http://hdl.handle.net/10.2312/3dor.20141050.053-060This paper proposes novel descriptors that integrate information from multiple views of a 3D object, called Temporal Ensemble of Shape Functions (TESF) descriptors. The TESF descriptors are built by combining per-view Ensemble of Shape Functions (ESF) descriptors with Spatio-Temporal Appearance (STA) descriptors. ESF descriptors provide a compact representation of ten different shape functions per object view (obtained by virtually rendering the object from different viewpoints), and STA descriptors efficiently combine ESF descriptors of multiple object views. The proposed descriptors are evaluated on two publicly available datasets, the 3D-Net database and the Princeton Shape Benchmark. They provide a good performance on both datasets, similar to that of the Spherical Harmonic Descriptor (SHD), with the advantage that because of their view-based nature the TESF descriptors might prove useful for the problem of object classification from limited viewpoints. Such property is of special interest in robotics where the agent is able to move around the object to improve single-view results.I.3.3 [Computer Graphics]Picture/Image GenerationLine and curve generationI.4.7 [Image Processing and Computer Vision]Feature MeasurementFeature representationI.5.4 [Pattern Recognition]ApplicationsComputer vision