Abstract
The most important application area of visual pattern recognition is design and development of a computer visions system wheather for robotics or for industrial inspection, capable of recognising and determining the portion of an object in a scene, particularly so when the objects are occluded. In this paper a new computational approach along with the computational results are presented based on the concept of differential geometry for recognition and position determination of partially occluded 2D rigid object and successful extension and implementation of the method for the 3D objects.For a partially occluded 2D objects in a scene a set of invarient local features are generated initially. Next, based upon matching of local features of the objects in a scene and the models which are considered as cognitive data base, a computer vision scheme is described using AI concept of hypothesis generation and verification of features for the best possible recognition. The method is successfully extended to the rea...
Published Version
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