DocumentCode
595248
Title
Invariant signatures for omnidirectional visual place recognition and robot localization in unknown environments
Author
Marie, Rodolphe ; Labbani-Igbida, O. ; Mouaddib, El Mustapha
Author_Institution
Modelisation, Inf. & Syst. Lab., Univ. of Picardie Jules Verne, Amiens, France
fYear
2012
fDate
11-15 Nov. 2012
Firstpage
2537
Lastpage
2540
Abstract
The paper introduces a novel approach to place representation for robot localization and mapping. It uses classical invariance theory while proposing an adaptive kernel to omnidirectional images and exploiting only the main significant visual information in the images. The approach is validated in real world robot exploration and localization and compared to color histograms.
Keywords
SLAM (robots); image colour analysis; image representation; mobile robots; object recognition; path planning; robot vision; adaptive kernel; classical invariance theory; color histograms; invariant signatures; omnidirectional images; omnidirectional visual place recognition; place representation; robot exploration; robot localization; robot mapping; unknown environments; Histograms; Image color analysis; Kernel; Robot sensing systems; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location
Tsukuba
ISSN
1051-4651
Print_ISBN
978-1-4673-2216-4
Type
conf
Filename
6460684
Link To Document