Computational Models for Cognitive Vision

Learn how to apply cognitive principlesto the problems of computer vision Computational Models for Cognitive Visionformulates the computational models forthecognitive principlesfound inbiologicalvision,and applies those modelsto computer visiontasks.Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few.The author'sultimate goalis toprovide a framework forcreation of amachine vision systemwith thecapability and versatility ofthe human vision. Written by Dr.HiranmayGhosh, the book takes readers through the basicprinciplesand the computational modelsforcognitive vision, Bayesian reasoning for perception and cognition, and otherrelatedtopics, beforeestablishing therelationship ofcognitive visionwiththemulti-disciplinaryfield broadly referred to as "artificial intelligence".The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots.The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision. Other topics covered in the book include: · knowledge representation techniques · evolution of cognitive architectures · deeplearning approachesfor visual cognition Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.