Title :
An algorithm for dense correspondence based on blended intrinsic map
Author :
Dan Kang;Xiuyang Zhao;Zhiang Chen;Mingjun Liu
Author_Institution :
School of Information Science and Engineering, University of Jinan, Jinan, China
Abstract :
The dense matching of 3-D meshes is an important research topic in the field of computer vision. In this paper, we present a layered matching pipeline based on the mixed corresponding grid dense matching algorithm. Firstly, this algorithm find an intrinsic map between two non-isometric, genus zero surfaces. Secondly, we use the nature of the bottom of the measure preserving distance to released the dense corresponding of surfaces. A set of experimental results show that the proposed method achieves better approximation accuracy than the ICP method.
Keywords :
"Shape","Iterative closest point algorithm","Geometry","Euclidean distance","Transforms","Heating","Area measurement"
Conference_Titel :
Image and Signal Processing (CISP), 2015 8th International Congress on
DOI :
10.1109/CISP.2015.7407932