Selective Visual Attention: Computational Models and Applications explores the intersection of artificial neural networks, artificial intelligence, vision science, and psychology to build computational models that mimic human vision. Aimed at advancing research in computer vision, this book provides an up-to-date introduction to visual attention, essential for developing powerful computer vision systems. It covers significance in vision research, psychological aspects, and existing computational models of visual attention, along with the authors’ contributions and applications in image and video processing tasks.

Targeted at graduate students, researchers in neural networks, image processing, machine learning, and biologically inspired model building, this book is also valuable for practicing engineers interested in applying image coding, video processing, machine vision, and brain-like robots to real-world systems. Its interdisciplinary approach makes it appealing to those with diverse interests in these fields.

Key highlights include:

• An introduction to the significance of visual attention research
• A review of existing computational models of visual attention
• The authors’ contributions and applications in image and video processing tasks

This book serves as a critical knowledge resource for developers working on image processing applications.