EDVD — Enhanced descriptor for visual and depth data

Many problems in computer vision and robotics rely on automatically determining point correspondences from two images. Due to issues such as illumination variations, uncontrolled acquisition conditions and noise, this is a challenging problem. This work presents a method that combines visual and shape information to perform point correspondences which is invariant to rotation and scaling transformations in the image and geometry domains. Experimental results show that our approach is a robust and computationally efficient technique compared with classic descriptors in the literature.