ISaR Projekt

"This paper proposes a bio-inspired visual motion estimation algorithm based on motion energy, along with its compact VLSI architecture using low-cost embedded systems. The algorithm mimics motion perception functions of retina, V1 and MT neurons in primate visual system. It involves operations of ternary edge extraction, spatiotemporal filtering, motion energy extraction, and velocity integration. Moreover, we propose the concept of confidence map to indicate the reliability of estimation results on each probing location. Our algorithm only involves additions and multiplications during runtime, which is suitable for low-cost hardware implementation. The proposed VLSI architecture employs multiple (frame-, pixel- and operation-) levels of pipeline and massively parallel processing arrays to boost the system performance. The array unit circuits are optimized to minimize hardware resource consumption. We have prototyped the proposed architecture on a low-cost FPGA platform (Zynq 7020) running at 53 MHz clock frequency. It achieved 30 frames per second real-time performance for velocity estimation on 160 × 120 probing locations. A comprehensive evaluation experiment showed that the estimated velocity by our prototype has relatively small errors (average Endpoint Error < 0.5 pixels and Angular Error < 10°) for most motion cases."

(Zitat und Quelle: IEEE Transactions on Circuits and Systems for Video Technology)