Active vision driven by a neuromorphic selective attention system
Daniel Sonnleithner, Giacomo Indiveri · 2015
Abstract In real world scenarios, guiding vision to focus on salient parts of the visual space is a computationally demanding tasks. Selective attention is a biolog-ically inspired strategy to cope with this problem, that can be used in engineered systems with limited resources. In active vision systems however, the stringent real-time requirements limit the space of solutions that can be achieved with conven-tional machine vision techniques and systems. We propose a hybrid approach where we combine a custom neuromorphic VLSI saliency-map based attention system with a conventional imager and a workstation, to implement both fast contrast-based saccadic eye movements in parallel with standard machine vision attention models using high-resolution color input images. We describe the system and present its response properties using basic control experiments. 1