Visual Saliency Based Natural Landmarks Detection under Unknown Environments

摘要

Natural landmark detection is a basis of mobile robots navigation to represent and recognize unknown environments.A saliency based adaptive natural landmarks detecting system is presented in this paper.Firstly the detail preserving sampling scheme is designed to create multi-scale image spaces where opponencies of color and texture are computed.And the Gabor filter,which can adjust parameters adaptively,is designed to analyze texture of all kinds of environments.At last the saliency map that points out where can be treated as natural landmark is created.Experiments show that this algorithm has better precision on detecting salient points and better repeatability including scale,rotation and viewpoint invariance.