Integrated Vision and Sensing for Human Sensory Augmentation

Abstract

The Carnegie Mellon University MURI project sponsored by ONR performs multi-disciplinary research in integrating vision algorithms with sensing technology for low-power, low-latency, compact adaptive vision systems. These are crucial features necessary for augmenting the human sensory system and enabling sensory driven information delivery. The project spans four subareas ranging from low to high level of vision: (1) smart filters, based on the Acousto-Optic Tunable Filter (AOTF) technology; (2) computational sensor methodology, which integrates raw sensing and computation by means of VLSI technology; (3) neural-network based saliency identification techniques for identifying the most useful information for extraction and display; and (4) visual learning methods for automatic signal-to-symbol mapping.