ABSTRACT
This paper presents a computational model for stereopsis. Laplacian of Gaussian filters are used to simulate ganglion cells and LGN cells and zero-crossings extracted provide spatial features in the visual scene. A set of one-octave Gabor filters is used to extract orientation information, which cover 0 to 60 cycles/degree interval in the human visual system. A Gaussian sphere model is used to map a 3D space onto two 2D image planes, which combines monocular cues with binocular cues in stereo matching. The determinant of the Jacobian of the mapping is derived and matching is performed using zero-crossings associated with their orientation information. The possibility of transferring the knowledge such as the probability of occurrence of visual scenes to the matching process from the mapping is discussed. Relaxation labelling is used as a co-operative process, which simulates binocular fusion and rivalry in the human visual process.
