3D surface point and wireframe reconstruction from multiview photographic images
Image and Vision Computing
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Very low bit-rate coding requires new paradigms that go well beyond pixel- and frame-based video representations. We introduce a novel content-based video representation using tridimensional entities: textured object models and pose estimates. The multiproperty object models carry stochastic information about the shape and texture of each object present in the scene. The pose estimates define the position and orientation of the objects for each frame. This representation is compact. It provides alternative means for handling video by manipulating and compositing three-dimensional (3-D) entities. We call this representation tridimensional video compositing, or 3DVC for short. We present the 3DVC framework and describe the methods used to construct incrementally the object models and the pose estimates from unregistered noisy depth and texture measurements. We also describe a method for video frame reconstruction based on 3-D scene assembly, and discuss potential applications of 3DVC to video coding and content-based handling. 3DVC assumes that the objects in the scene are rigid and segmented. By assuming segmentation, we do not address the difficult questions of nonrigid segmentation and multiple object segmentation. In our experiments, segmentation is obtained via depth thresholding. It is important to notice that 3DVC is independent of the segmentation technique adopted. Experimental results with synthetic and real video sequences where compression ratios in the range of 1:150-1:2700 are achieved demonstrate the applicability of the proposed representation to very low bit-rate coding