DocumentCode :
2020373
Title :
A rectification algorithm for un-calibrated multi-view images based on SIFT features
Author :
Zhang Yang ; Ping, An ; He, Wang ; haoyang, Zhang
Author_Institution :
Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China
fYear :
2010
fDate :
23-25 Nov. 2010
Firstpage :
143
Lastpage :
147
Abstract :
In this paper, we present an efficient rectification algorithm for un-calibrated multi-view images based on SIFT (Scale-invariant feature transform) feature matching. Un-calibrated rectification is necessary for some specific occasions and we extend generic stereo pair rectification to multi-view camera array with projection shift method. We bring in SIFT algorithm to extract and match features (key points) automatically. Block-division features extraction method is proposed and RANSAC is used to improve precision of rectifying transformation. From the experiments, we find that our method is effective to rectify parallel cameras array. Rectified images have uniform horizontal disparities and the vertical mismatches between adjacent views are eliminated.
Keywords :
feature extraction; image matching; stereo image processing; transforms; RANSAC; block-division feature extraction method; multiview camera array; projection shift method; scale-invariant feature transform feature matching; stereo pair rectification; uncalibrated multiview images; uncalibrated rectification; Algorithm design and analysis; Arrays; Cameras; Feature extraction; Pixel; Three dimensional displays; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Audio Language and Image Processing (ICALIP), 2010 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-5856-1
Type :
conf
DOI :
10.1109/ICALIP.2010.5684990
Filename :
5684990
Link To Document :
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