DocumentCode :
594729
Title :
Probabilistic depth map fusion for real-time multi-view stereo
Author :
Duan Yong ; Pei Mingtao ; Jia Yunde
Author_Institution :
Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
368
Lastpage :
371
Abstract :
In this paper we propose a probabilistic method for fusing depth maps in real time for wide-baseline situation. We treat the depth map fusion as a problem of probability density function (pdf) estimation. The original point cloud, instead of the reprojected depth map, is used to estimate the pdf, and a mathematical expectation computation method is proposed to reduce the complexity of the method. Experimental results show that the proposed method can get the fused depth map in real time, and is very promising for fusing depth maps from multiple depth cameras with sparsely distributed viewpoints.
Keywords :
cameras; computational complexity; image fusion; probability; real-time systems; stereo image processing; complexity reduction; mathematical expectation computation method; multiple depth cameras; pdf estimation; point cloud; probabilistic depth map fusion; probabilistic method; probability density function estimation; real-time multiview stereo; Cameras; Complexity theory; Estimation; Gaussian distribution; Probabilistic logic; Probability density function; Real-time systems;
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 :
6460148
Link To Document :
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