Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1020637704729
Title: Least committed splines in 3D modelling of free form objects from intensity images
Authors: Sengupta, K. 
Burman, P.
Gupta, S.
Keywords: Affine projection
Bicubic splines
Heirarchical splines
Object modeling
Issue Date: Sep-2002
Source: Sengupta, K., Burman, P., Gupta, S. (2002-09). Least committed splines in 3D modelling of free form objects from intensity images. Journal of Mathematical Imaging and Vision 17 (2) : 175-186. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1020637704729
Abstract: Generating 3D models of objects from video sequences is an important problem in many multimedia applications ranging from teleconferencing to virtual reality. In this paper, we present a method of estimating the 3D face model from a monocular image sequence, using a few standard results from the affine camera geometry literature in computer vision, and spline fitting techniques using a modified non parametric regression technique. We use the bicubic spline functions to model the depth map, given a set of observation depth maps computed from frame pairs in a video sequence. The minimal number of splines are chosen on the basis of the Schwartz's Criterion. We extend the spline fitting algorithm to hierarchical splines. Note that the camera calibration parameters and the prior knowledge of the object shape is not required by the algorithm. The system has been successfully demonstrated to extract 3D face structure of humans as well as other objects, starting from their image sequences.
Source Title: Journal of Mathematical Imaging and Vision
URI: http://scholarbank.nus.edu.sg/handle/10635/56484
ISSN: 09249907
DOI: 10.1023/A:1020637704729
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