Vision research has uncovered computational principles that generalize across species and
brain area. However, these biological mechanisms are not frequently implemented in …

Computational modeling of the primate visual system yields insights of potential relevance to
some of the challenges that computer vision is facing, such as object recognition and …

Studies in biological vision have always been a great source of inspiration for design of
computer vision algorithms. In the past, several successful methods were designed with …

Brains and sensory systems are characterized by limited bandwidth and computational
resources. At any point in time, we can focus our attention only to a limited set of features or …

The term space-variant vision was introduced in the late 1980s to refer to sensor
architectures based on a smooth variation of resolution across the workspace, like that of the …

Hierarchical processing is receiving increased attention as a powerful technique for image
processing and scene understanding in active vision. Machine vision systems have been …

Brains are characterized by limited bandwidth and computational resources. At any point in
time, we can focus our attention only to a limited set of features or objects. One of the most …

Building a general-purpose, real-time active vision system completely based on biological
models is a great challenge. We apply a number of biologically plausible algorithms which …

Abstract Space-variant sampling of visual input is ubiquitous in the higher vertebrate brain,
because a large input space may be processed with high peak precision without requiring …

In this review, we discuss the impact (or lack thereof) biologically motivated vision has had
on computer vision in the last decades. We then summarize a number of computer vision …