TY - JOUR
T1 - Edge-preserving joint motion-disparity estimation in stereo image sequences
AU - Min, Dongbo
AU - Kim, Hansung
AU - Sohn, Kwanghoon
N1 - Funding Information:
This work is financially supported by the Ministry of Education and Human Resources Development (MOE), the Ministry of Commerce, Industry and Energy (MOCIE) and the Ministry of Labor (MOLAB) through the fostering project of the Lab of Excellency, and is in part supported by the MIC (Ministry of Information and Communication), Korea under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Assessment)" (IITA-2005-(C1090-0502-0027)).
PY - 2006/3
Y1 - 2006/3
N2 - An energy-based joint motion and disparity estimation algorithm with an anisotropic diffusion operator is proposed to yield correct and dense displacement vectors. We propose two energy models; the joint estimation model and the simultaneous joint estimation model. In the joint estimation model, we compute the initial disparity in the current frame with the joint estimation constraint, using the left and right motions and the disparity in the previous frame; therefore, the model is prevented from being trapped in the local minima. Then, we regularize this disparity by using our proposed energy model. In the simultaneous joint estimation model, we propose an energy functional that consists of fidelity and smoothing terms for the left and right motions and the joint data terms. We estimate the left and right motions simultaneously in order to increase correctness. We use the Euler-Lagrange equation with variational methods and solve the equation with the finite difference method (FDM) to minimize the energy model. Experimental results show that the proposed algorithm provides accurate motion-disparity maps that reflect the constraints of motion and disparity, and preserve the discontinuities of the object boundaries well.
AB - An energy-based joint motion and disparity estimation algorithm with an anisotropic diffusion operator is proposed to yield correct and dense displacement vectors. We propose two energy models; the joint estimation model and the simultaneous joint estimation model. In the joint estimation model, we compute the initial disparity in the current frame with the joint estimation constraint, using the left and right motions and the disparity in the previous frame; therefore, the model is prevented from being trapped in the local minima. Then, we regularize this disparity by using our proposed energy model. In the simultaneous joint estimation model, we propose an energy functional that consists of fidelity and smoothing terms for the left and right motions and the joint data terms. We estimate the left and right motions simultaneously in order to increase correctness. We use the Euler-Lagrange equation with variational methods and solve the equation with the finite difference method (FDM) to minimize the energy model. Experimental results show that the proposed algorithm provides accurate motion-disparity maps that reflect the constraints of motion and disparity, and preserve the discontinuities of the object boundaries well.
KW - Anisotropic diffusion operator
KW - Energy-based joint estimation
KW - Euler-lagrange equation
KW - FDM
KW - Simultaneous joint estimation
UR - http://www.scopus.com/inward/record.url?scp=33644950269&partnerID=8YFLogxK
U2 - 10.1016/j.image.2005.10.003
DO - 10.1016/j.image.2005.10.003
M3 - Article
AN - SCOPUS:33644950269
SN - 0923-5965
VL - 21
SP - 252
EP - 271
JO - Signal Processing: Image Communication
JF - Signal Processing: Image Communication
IS - 3
ER -