Saccadic object recognition with an active vision system

Proposes an active vision system for saccadic camera gaze shifts and explorative scene analysis as a new integral approach to image understanding. The model consists of two sensory subsystems: preattentive peripheral feature detection and high resolution foveal image identification based on a hypercolumnar representation. Visual objects are non-explicitly stored in two sparsely coded associative memories separating fixation locations for identities of foveal views. An egocentric interest map integrates bottom-up and top-down information sources and decides when to generate a camera movement. A selective masking of preattentive processes supports a cooperation with cognitive object recognition. The system is easily extendible, copes with occlusions and distortions and can be driven in different modes for exploration tasks. This model is able to perform visual search and reproduce findings in the human visual system