In this paper we present a method of combining stereo and shape-from-shading information, taking account of the local reliability of each shape estimate. Local estimates of disparity and orientation are modelled using Gaussian distributions. A Gaussian-Markov random field is used to represent the disparity-map, taking into account interactions between disparity measurements and surface orientation, and the MAP estimate found using belief propagation. Local estimates of the precision of disparities and surface normals are found and used to control the process so that the most accurate data source is used in each region. We assess the performance of our approach using both synthetic and real stereo pairs, and compare against ground truth.
|Number of pages||4|
|Publication status||Published - 2008|
|Event||19th International Conference on Pattern Recognition, ICPR 2008 - Tampa, FL, USA United States|
Duration: 8 Dec 2008 → 11 Dec 2008
|Conference||19th International Conference on Pattern Recognition, ICPR 2008|
|Country||USA United States|
|Period||8/12/08 → 11/12/08|
Fincham Haines, T., & Wilson, R. C. (2008). Combining shape-from-shading and stereo using Gaussian-Markov random fields. Paper presented at 19th International Conference on Pattern Recognition, ICPR 2008, Tampa, FL, USA United States.