Abhranil Das, Geisler Lab & Dept. of Physics

 

  

Abstract: Camouflage is an amazing feat of evolution, but also impressive is the ability of biological visual systems to detect them. In this thesis, we investigate the principles of human detection of maximally-camouflaged objects, i.e. whose texture is a random sample of the background texture. We develop a theory and model that extracts the relevant information in the image, and uses biologically plausible computations on them for detection. We then present a series of experiments that measured human camouflage detection ability along different aspects and conditions of the detection task, such as across different textures and shapes, and describe how we use our models to understand these findings.