Surface segmentation and modeling of 3D polygonal objects from stereoscopic image pairs
An approach to automatically generate 3D polygonal models from stereoscopic image pairs of piecewise planar objects is presented. Dense disparity maps are computed by constrained epipolar block matching. Local surface orientations are computed from the quantized disparity map using a spline approximation under explicit consideration of quantization noise. The local surface orientation is then clustered into regions of similar surface orientation to find the dominant object planes. A photo realistic 3D polygonal model of the object is constructed by fitting planar polygons to the surfaces and by mapping original image texture to the model.