Point clouds produced by either 3D scanners or multi-view images are often imperfect and contain noise outliers. This paper presents an end-to-end robust spherical harmonics approach to classifying objects. The proposed framework first uses the voxel grid of concentric spheres learn features over unit ball. We then limit order level suppress effect In addition, entire classification operation i...

With the development of vision and haptic sensor technologies, robots have become increasingly capable perceiving their external environments. Although machine haptics surpassed humans in some aspects perception, it is difficult for to describe objects from multiple viewpoints by using a combination visual modalities. In this paper, we use convolutional neural networks separately extract featur...