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The human visual system
is able to
The
correct and fast estimation of disparities is a difficult problem. Besides
disparities, various additional image variations occur between the left and
right view of a scene. Differences might be caused by occlusions of objects, specular reflections, which move independently of the
surfaces of objects, sensor noise, and various other causes. Stereovision has long
been researched; common computational approaches include feature-based,
area-based and phase-based methods. All these methods have their intrinsic problems, caused by the very assumptions
inherent in these approaches. On these pages, a simple and fast algorithm is described, which is very
different from these classical methods. It is based on the detection of
coherence between simple disparity units modeling
complex cells in human visual cortex. The neural network implementing the
algorithm has some unique properties: it has an internal verification measure, indicating for example areas of
occlusion, and it creates as a by-product of the disparity calculations the cyclopean view of the scene. Coherence-Detection and Disparity
Maps by Spiking Neurons
More infos:
- Please note that patents are pending for some of the algorithms
described here. - |