Detection of camouflaged textures

To study the importance of edges in detecting camouflaged objects.

Detection of objects in natural images.

We developed a near-optimum detector for objects embedded in natural images. In experiments we tested the algorithm against the performance of human observers.

Optimal search for objects embedded in natural images.

Searching the environment in a fast and efficient manner is a critical capability for humans and many other animals. Normally, multiple fixations are used to identify and localize targets. However, in the special case of covert search the target must be identified and localized within a single fixation. Here we present a theory of covert search that takes into account the statistical variation in background images, the falloff in resolution and sampling with retinal eccentricity, the increase in intrinsic location uncertainty with retinal eccentricity, and the prior probability of target presence and target location in the image.