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Numérisation 3D de visages par une approche de super-résolution spatio-temporelle non-rigide

Karima Ouji 1 
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : 3D face measurement is increasingly demanded for many applications such as bio-metrics, animation and facial surgery. Current solutions often employ a structured light camera/projector device to overcome the relatively uniform appearance of skin. Depth in-formation is recovered by decoding patterns of the projected structured light. One of the most widely used structured-light coding is sinusoidal phase shifting which allows a 3Ddense resolution. Current solutions mostly utilize more than three phase-shifted sinusoidal patterns to recover the depth information, thus impacting the acquisition delay. They further require projector-camera calibration whose accuracy is crucial for phase to depth estimation step. Also, they need an unwrapping stage which is sensitive to ambient light, especially when the number of patterns decreases. An alternative to projector-camera systems consists of recovering depth information by stereovision using a multi-camera system. A stereo matching step finds correspondence between stereo images and the 3D information is obtained by optical triangulation. However, the model computed in this way generally is quite sparse. To up sample and denoise depth images, researchers looked into super-resolution techniques. Super-resolution was especially proposed for time-of-flight cameras which have very low data quality and a very high random noise. This thesis proposes a3D acquisition solution with a 3D space-time non-rigid super-resolution capability, using a calibrated multi-camera system coupled with a non calibrated projector device, which is particularly suited to 3D face scanning, i.e. rapid and easily movable. 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 the assets of stereovision and structured light but also overcomes their weaknesses. The super-resolution scheme involves a 3D non-rigid registration for 3D artifacts correction in the presence of small non-rigid deformations as facial expressions.
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Karima Ouji. Numérisation 3D de visages par une approche de super-résolution spatio-temporelle non-rigide. Autre. Ecole Centrale de Lyon, 2012. Français. ⟨NNT : 2012ECDL0013⟩. ⟨tel-00923193⟩

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