A Knowledge Driven Computational Visual Attention Model
Computational Visual System face complex processing problems as there is a large amount of information to be processed and it is difficult to achieve higher efficiency in par with human system. In order to reduce the complexity involved in determining the saliency region, decomposition of image into several parts based on specific location is done and decomposed part is passed for higher level computations in determining the saliency region with assigning priority to the specific color in RGB model depending on application. These properties are interpreted from the user using the Natural Language Processing and then interfaced with vision using Language Perceptional Translator (LPT). The model is designed for a robot to search a specific object in a real time environment without compromising the computational speed in determining the Most Salient Region.
Keywords: Visual Attention, Saliency, Language Perceptional Translator, Vision
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