LOW-POWER, REAL-TIME OBJECT-RECOGNITION PROCESSORS FOR MOBILE VISION SYSTEMS

Abstract

A new low-power object-recognition processor achieves real-time robust recognition, satisfying modern mobile vision systems' requirements. The authors introduce an attention-based object-recognition algorithm for energy efficiency, a heterogeneous multicore architecture for data- and thread-level parallelism, and a network on a chip for high on-chip bandwidth. The fabricated chip achieves 30 frames/second throughput and an average 320 MW power consumption on test 720P video sequences, yielding 640 GOPS/W and 10.5 NJ/PIXEL energy efficiency.