A vision system was built using a behavior-based model, the subsumption architecture. The so-called active eye moves the camera’s axis through the environment, detecting areas with high concentration of edges, with the help of a kind of saccadic movement. The design and implementation process is detailed in the article, paying particular attention to the fovea-like sensor structure which enables the active eye to efficiently use local information to control its movements. Numerical measures for the eye’s behavior were developed, and applied to evaluate the incremental building process and the effects of the saccadic movements on the whole system. A higher level behavior was also implemented, with the purpose of detecting long straight edges in the image, producing pictures similar to hand drawings. Robustness and efficiency problems are addressed at the end of the paper. The results seem to prove that interesting behaviors can be achieved using simple vision methods and algorithms, if their results are properly interconnected and timed.
Reconfigurable foveated active vision system
