Title :
MRF and DP based specular surface reconstruction
Author :
Ravindra Redddy, K. ; Namboodiri, Anoop
Author_Institution :
Center for Visual Inf. Technol., Int. Inst. of Inf. Technol., Hyderabad, India
Abstract :
This paper addresses the problem of reconstruction of specular surfaces using a combination of Dynamic Programming and Markov Random Fields formulation. Unlike traditional methods that require the exact position of environment points to be known, our method requires only the relative position of the environment points to be known for computing approximate normals and infer shape from them. We present an approach which estimates the depth from dynamic programming routine and MRF stereo matching and use MRF optimization to fuse the results to get the robust estimate of shape. We used smooth color gradient image as our environment texture so that shape can be recovered using just a single shot. We evaluate our method using synthetic experiments on 3D models like Stanford bunny and show the real experiment results on golden statue and silver coated statue.
Keywords :
Markov processes; dynamic programming; image colour analysis; image matching; image reconstruction; image texture; random processes; stereo image processing; 3D models; DP based specular surface reconstruction; MRF optimization; MRF stereo matching; Markov random field formulation; Stanford bunny; dynamic programming; environment image texture; golden statue; robust shape estimation; silver coated statue; smooth color gradient image; Dynamic programming;
Conference_Titel :
Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), 2013 Fourth National Conference on
Conference_Location :
Jodhpur
Print_ISBN :
978-1-4799-1586-6
DOI :
10.1109/NCVPRIPG.2013.6776239