A stereo model using LoG and Gabor filtering

This paper presents a computational model for stereopsis. Laplacian of Gaussian filters are used to extract spatial features and a set of one-octave Gabor filters is used to extract orientation information from a scene. A mapping from a 3D space onto two 2D image planes is derived using a Gaussian sphere model. The determinant of the Jacobian of the mapping is derived and matching is performed using zero-crossings associated with their orientation information. Relaxation labelling is used as a co-operative process for solving the correspondence problem.