Constructing 3D models from video is one of the most important problems in computer vision. We propose a novel 3D face modeling approach from monocular video captured by a conventional camera. An algorithm is proposed to estimate the head pose by comparing the edges of video frame, and the contours extracted from a generic face model. A generic 3D face model is assumed to be the initial estimate of the true 3D model. The generic face model is adapted to the actual 3D face model by global and local deformations. An affine model is used for global deformation. The 3D model is locally deformed by computing the optimal perturbations of a sparse set of control points using a stochastic search optimization method. The deformations are integrated over a set of poses in the video sequence, leading to an accurate 3D model.
Author: Gupta, Himaanshu
Source: University of Maryland
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