基于形变模型由立体序列图象恢复物体的3D形状

3D Shape Recovery from a Sequence of Stereo Images Based on Deformable Models

结合立体视觉和形变模型提出了一种新的物体形状的恢复方法。采用立体视觉方法导出物体表面的坐标;利用光流模型估计物3D3D体的运动,根据此运动移动形变模型,使其对准物体的表面块;由形变模型将由各幅图象得到的离散的点融为一起,得到物体的表面3D3D形状。实验结果表明该方法能用于形状复杂的物体恢复。

A method is presented for recovering the 3D shape of objects from a sequence of stereo images, which integrates shape from stereo and deformable model . Scene point correspondence required for deriving the depth of the scene point is determined using Immune algorithm .The object shape is described by a deformable surface model, which successively fuses surface patches computed from each pair of stereo images through deformation. Aligned with the input surface path according to the object or camera motion, the model is deformed by attracting its corresponding surface towards the input surface patch. Object motion between successive pairs of stereo images is estimated by tracking a set of image features. Experimental results are also included to show the feasibility of our new method.