Efficient object shape recovery via slicing planes

Recovering the three-dimensional (3D) object shape lies as an unresolved and active research topic on the crosssection of computer vision, photogrammetry and bioinformatics. Although various techniques have been developed for this topic, the computational complexity and the constraints introduced to overcome the problems have limited their applicability in real world scenarios. In this paper, we propose a method that is based on the projective geometry between the object space and silhouette images taken from multiple viewpoints. The approach eliminates the problems related to dense feature point matching and camera calibration that are generally adopted by many state of the art shape reconstruction methods. The object shape is reconstructed by establishing a set of hypothetical planes slicing the object volume and estimating the projective geometric relations between the images. The experimental results show that the 3D object shape can be generated by applying minimal constraints.

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Po-Lun Lai, Alper Yilmaz
• Keywords: Computer Vision, CVPR 2008, Object Shape, Object Space, Object Volume, Projective Geometric Relations, Shape Reconstruction Methods