Title :
A novel depth estimation method for uncalibrated stereo images
Author :
Loghman, Maziar ; Zarshenas, Amin ; Kwang-Hoon Chung ; Yunsik Lee ; Joohee Kim
Author_Institution :
Illinois Inst. of Technol., Chicago, IL, USA
Abstract :
In this paper, a depth map estimation algorithm that performs stereo matching without explicit image rectification has been proposed. In the proposed method, the fundamental matrix is estimated by using Random Sample Consensus and the 8-point algorithm. Then, the epilolar line equation obtained by the projective mapping is derived and the search for point correspondence is performed along the epilolar line. Simulation results show that the proposed method produces accurate depth maps for uncalibrated stereo images with reduced computational complexity.
Keywords :
computational complexity; estimation theory; image matching; stereo image processing; computational complexity; depth map estimation algorithm; epilolar line; epilolar line equation; fundamental matrix; image rectification; novel depth estimation method; projective mapping; random sample consensus; stereo matching; uncalibrated stereo images; Algorithm design and analysis; Frequency locked loops; Simulation; Streaming media; Switches; Venus; Workstations; Stereo vision; depth estimation; fundamental matrix; image rectification;
Conference_Titel :
SoC Design Conference (ISOCC), 2014 International
DOI :
10.1109/ISOCC.2014.7087688