TY - GEN
T1 - Inverse lighting for non-homogeneous objects from color and depth image using wavelet representation
AU - Choe, Junsuk
AU - Shim, Hyunjung
N1 - Publisher Copyright:
© 2015 SPIE-IS & T.
Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.
PY - 2015
Y1 - 2015
N2 - This paper provides a novel approach to estimating the lighting given a pair of color and depth image of non-homogeneous objects. Existing methods can be classified into two groups depending on the lighting model, either the basis model or point light model. In general, the basis model is effective for low frequency lighting while the point model is suitable for high frequency lighting. Later, a wavelet based method combines the advantages from both sides of the basis model and point light model. Because it represents all frequency lighting efficiently, we use the wavelets to reconstruct the lighting. However, all of the previous methods cannot reconstruct lighting from non-homogeneous objects. Our main contribution is to process the non-homogeneous object by dividing it into multiple homogeneous segments. From these segments, we first initialize material parameters and extract lighting coefficients accordingly. We then optimize material parameters with the estimated lighting. The iteration is repeated until the estimated lighting converged. To demonstrate the effectiveness of our method, we conduct six different experiments corresponding to the different number, size, and position of lighting. Based on the experiment study, we confirm that our algorithm is effective for identifying the light map.
AB - This paper provides a novel approach to estimating the lighting given a pair of color and depth image of non-homogeneous objects. Existing methods can be classified into two groups depending on the lighting model, either the basis model or point light model. In general, the basis model is effective for low frequency lighting while the point model is suitable for high frequency lighting. Later, a wavelet based method combines the advantages from both sides of the basis model and point light model. Because it represents all frequency lighting efficiently, we use the wavelets to reconstruct the lighting. However, all of the previous methods cannot reconstruct lighting from non-homogeneous objects. Our main contribution is to process the non-homogeneous object by dividing it into multiple homogeneous segments. From these segments, we first initialize material parameters and extract lighting coefficients accordingly. We then optimize material parameters with the estimated lighting. The iteration is repeated until the estimated lighting converged. To demonstrate the effectiveness of our method, we conduct six different experiments corresponding to the different number, size, and position of lighting. Based on the experiment study, we confirm that our algorithm is effective for identifying the light map.
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U2 - 10.1117/12.2083027
DO - 10.1117/12.2083027
M3 - Conference contribution
AN - SCOPUS:84926630192
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Proceedings of SPIE-IS and T Electronic Imaging - Computational Imaging XIII
A2 - Bouman, Charles A.
A2 - Sauer, Ken D.
PB - SPIE
T2 - Computational Imaging XIII
Y2 - 10 February 2015 through 11 February 2015
ER -