Recognition of partially occluded objects with back-propagation neural network

摘要

The problem of occlusion in a two-dimensional scene introduces errors into many existing vision algorithms that cannot be resolved. Occlusion occurs where two or more objects in a given image touch or overlap one another. Since occlusion will be present in all but the most constrained environment, the recognition of partially occluded objects is important for industrial machine vision applications to solve real problems in the military domain and in factory automation.