A maximum likelihood stereo algorithm
Computer Vision and Image Understanding
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
A 3D Facial Expression Database For Facial Behavior Research
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Resolution Enhancement of PMD Range Maps
Proceedings of the 30th DAGM symposium on Pattern Recognition
A Self-Calibrating Method for Photogeometric Acquisition of 3D Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Point Set Registration: Coherent Point Drift
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast and robust multiframe super resolution
IEEE Transactions on Image Processing
Laser scanner super-resolution
SPBG'06 Proceedings of the 3rd Eurographics / IEEE VGTC conference on Point-Based Graphics
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Low-cost and high-accuracy 3D face measurement is becoming increasingly important in many computer vision applications including face recognition, facial animation, games, orthodontics and aesthetic surgery. In most cases fringe projection based systems are used to overcome the relatively uniform appearance of skin. These systems employ a structured light camera/projector device and require explicit user cooperation and controlled lighting conditions. In this paper, we propose a 3D acquisition solution with a 3D space-time non-rigid super-resolution capability, using three calibrated cameras coupled with a non calibrated projector device, which is particularly suited to 3D face scanning, i.e. rapid, easily movable and robust to ambient lighting variation. The proposed solution is a hybrid stereovision and phase-shifting approach, using two shifted patterns and a texture image, which not only takes advantage of stereovision and structured light, but also overcomes their weaknesses. The super-resolution scheme involves a shape+texture 3D non-rigid registration for 3D artifacts correction in the presence of small non-rigid deformations as facial expressions.