Please use this identifier to cite or link to this item: https://doi.org/10.1109/CVPR.2012.6247680
Title: A biquadratic reflectance model for radiometric image analysis
Authors: Shi, B.
Tan, P. 
Matsushita, Y.
Ikeuchi, K.
Issue Date: 2012
Citation: Shi, B.,Tan, P.,Matsushita, Y.,Ikeuchi, K. (2012). A biquadratic reflectance model for radiometric image analysis. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition : 230-237. ScholarBank@NUS Repository. https://doi.org/10.1109/CVPR.2012.6247680
Abstract: Radiometric image analysis methods heavily rely on reflectance models. Due to the complexity of real materials, methods based on simple models such as the Lambertian model often suffer from inaccuracy. On the other hand, more advanced models such as the Cook-Torrance model severely complicate the analysis problem. We tackle this dilemma by focusing on the low-frequency component of the reflectance. We propose a compact biquadratic reflectance model to represent the reflectance of a broad class of materials precisely in the low-frequency domain. We validate our model by fitting to both existing parametric models and non-parametric measured data, and show that our model outperforms existing parametric diffuse models. We show applications of reflectometry using general diffuse surfaces and photometric stereo for general isotropic materials. Experimental results show the effectiveness of our biquadratic model and its usefulness in radiometric image analysis. © 2012 IEEE.
Source Title: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/68719
ISBN: 9781467312264
ISSN: 10636919
DOI: 10.1109/CVPR.2012.6247680
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