Motion and Structure from Orthographic Projections
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition by Linear Combinations of Models
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
3D motion recovery via affine epipolar geometry
International Journal of Computer Vision
Surface fitting with hierarchical splines
ACM Transactions on Graphics (TOG)
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Discontinuity-preserving surface reconstruction using stochastic differential equations
Computer Vision and Image Understanding
Animated heads from ordinary images: a least-squares approach
Computer Vision and Image Understanding
Automatic Creation of 3D Facial Models
IEEE Computer Graphics and Applications
Acquiring 3-D Models from Sequences of Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parametrized structure from motion for 3D adaptive feedback tracking of faces
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
An Affine Coordinate Based Algorithm for Reprojecting the Human Face for Identification Tasks
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
Using Differential Constraints to Generate a 3D Face Model from Stereo
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
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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.