CogVis: attention-driven cognitive architecture for visual change detection

Shailesh Deshpande, Arcot Sowmya, Piyush Yadav, Shamsuddin Ladha, Priyanka Verma, Karthikeyan Vaiapury, Jay Gubbi, P. Balamuralidhar

Abstract: The role played by attention in the increasingly important area of change detection is well recognized. The construction of automated visual change detection systems will benefit from an architecture based on sound cognitive principles. This paper proposes an attention-driven cognitive vision architecture for change detection and shows its utility with a remote sensing case study.