shape of the tensor defines the type of information captured point curve or surface element and its size represents the saliency by saliency the perceived importance or confidence of the probable structures such as surfaces curves junctions and regions are determined for instance a point on a smooth surface is represented by a tensor in the shape of an elongated ellipsoid stick tensor with its major axis along the surface normal the input tokens are first encoded as tensors a point is encoded as a 3 d ball tensor for the purpose of coherent feature extraction a saliency field can be computed using the tensor voting procedure at any given point votes are casted by all other data points using voting fields derived from the fundamental 2 d stick voting kernel developed by medioni et al the magnitude of the vote decays with distance and curvature according to the following equation where d is the distance along the smooth path arc length u03c1 is the curvature of the path and u03c3 is the scale of the voting field that essentially controls the size of the voting neighborhood and the strength of the votes vote accumulation is performed by tensor addition or equivalently by addition of 3 u00d7 3 matrices in the 3 d case therefore it is computationally inexpensive surfaces are extracted.