DocumentCode :
399291
Title :
A locally optimized scene reconstruction from three uncalibrated color images
Author :
Sham, Alfred H K ; Wong, Andrew K C
Author_Institution :
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
Volume :
2
fYear :
2003
fDate :
27-31 Oct. 2003
Firstpage :
1296
Abstract :
This paper presents a new robust scene-recognition algorithm using points and lines in three uncalibrated color images under natural or artificial lighting without knowing the poses of the camera. Local optimization is employed by the algorithm in finding point matches to guarantee accuracy in the case when object surface is extremely uneven of having abrupt changes, thus causing a wide range of point movements between consecutive images. The algorithm is iterated to obtain maximum features until no improvement can be achieved. Experiments using a large number of images show excellent performance by this new algorithm.
Keywords :
feature extraction; image colour analysis; image reconstruction; image sequences; lighting; optimisation; artificial lighting; lines; local optimization; natural lighting; object surface; optimized scene recognition; points; uncalibrated color images; Cameras; Color; Design engineering; Image reconstruction; Iterative algorithms; Karhunen-Loeve transforms; Layout; Pixel; Robustness; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on
Print_ISBN :
0-7803-7860-1
Type :
conf
DOI :
10.1109/IROS.2003.1248824
Filename :
1248824
Link To Document :
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