Inspired by Weber's Law, this paper proposes a simple, yet very powerful and robust local descriptor, Weber Local Descriptor (WLD). It is based on the fact that human percept...
Jie Chen, Shiguang Shan, Guoying Zhao, Xilin Chen,...
In this paper, we propose a novel supervised hierarchical sparse coding model based on local image descriptors for classification tasks. The supervised dictionary training is perf...
We previously presented an image registration method, referred to hierarchical attribute matching mechanism for elastic registration (HAMMER), which demonstrated relatively high a...
In this paper we propose the first version of FAIR, a low-dimensional image neighborhood descriptor that shows performance comparable to SIFT introduced by Lowe. The dimension of F...
We propose an approach for detecting objects in large-scale range datasets that combines bottom-up and top-down processes. In the bottom-up stage, fast-to-compute local descriptors...
Alexander Patterson, Philippos Mordohai, Kostas Da...