Fast Color/Texture Segmentation For Outdoor Robots

被引：0
|
作者：
Blas, Morten Rufus [1 ]
Agrawal, Motilal [2 ]
Sundaresan, Aravind [2 ]
Konolige, Kurt [2 ]
机构：
[1] DTU, Dept Elect Engn, Lyngby, Denmark
[2] SRI Internat, Artificial Intelligent Ctr, Menlo Pk, CA USA
来源：
2008 IEEE/RSJ INTERNATIONAL CONFERENCE ON ROBOTS AND INTELLIGENT SYSTEMS, VOLS 1-3, CONFERENCE PROCEEDINGS | 2008年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a fast integrated approach for online segmentation of images for outdoor robots. A compact color and texture descriptor has been developed to describe local color and texture variations in an image. This descriptor is then used in a two-stage fast clustering framework using K-means to perform online segmentation of natural images. We present results of applying our descriptor for segmenting a synthetic image and compare it against other state-of-the-art descriptors. We also apply our segmentation algorithm to the task of detecting natural paths in outdoor images. The whole system has been demonstrated to work online alongside localization, 3D obstacle detection, and planning.
引用
收藏
页码：4078 / +
页数：2
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