Title
Self-rectification and depth estimation of stereo video in a real-time smart camera system
Abstract
This paper presents a self-rectification stereo vision system based on a real-time, low power, and wireless smart camera platform. The proposed self-rectification method is suitable for an embedded parallel stereo system, where the epipolar lines are parallel to the image scan lines. The stereo images are first aligned by applying 1D signature matching. Then the alignment is refined based on the quality of the disparity measurement. The rectification method can be applied both offline and online. The major advantage of this rectification method is that no clean background is needed during the rectification process. After the rectification, the conjugate epipolar line is collinear. The dense matching method is implemented to achieve the depth map. This depth map provides a tool for segmentation. The application runs in an SIMD video-analysis processor, IC3D, at 30 fps and handles disparity up to 37 pixels in CIF (320times240 pixels) mode.
Year
DOI
Venue
2008
10.1109/ICDSC.2008.4635721
ICDSC
Keywords
Field
DocType
depth map,parallel processing,video signal processing,stereo image alignment,depth estimation,image matching,intelligent sensors,image segmentation,1d signature matching,embedded parallel stereo system,self-rectification stereo vision system,smart camera,real-time wireless smart camera system,collinear conjugate epipolar line,cif mode,embedded system,dense matching method,simd video-analysis processor,real-time,wireless sensor networks,self-rectification,embedded systems,stereo image processing,stereo vision,disparity measurement quality,pixel,real time,sensors,real time systems,estimation
Stereo camera,Computer vision,Computer graphics (images),Epipolar geometry,Computer science,Stereopsis,Image rectification,Smart camera,Image segmentation,Artificial intelligence,Depth map,Computer stereo vision
Conference
ISBN
Citations 
PageRank 
978-1-4244-2665-2
1
0.40
References 
Authors
4
4
Name
Order
Citations
PageRank
Xinting Gao111910.60
Richard P. Kleihorst219420.73
Peter B. L. Meijer351.27
Ben Schueler4463.12