Stereo Vision Using Computing Architecture Inspired by the Brain

Our Brain-Inspired Computing group at IBM Research-Almaden will be presenting at the 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018) our most recent paper titled "A Low Power, High Throughput, Fully Event-Based Stereo System." The paper describes an end-to-end stereo vision system that uses exclusively spiking neural network computation and can run on neuromorphic hardware with a live streaming spiking input. Inspired by the human vision system, it uses a cluster of IBM TrueNorth chips and a pair of digital retina sensors (also known as Dynamic Vision Sensors, DVS) to extract the depth of rapidly moving objects in a scene. Our system captures scenes in 3D with low power, low latency and high throughput, which has the potential to advance the design of intelligent systems. FIGURE 1: A fully event-based stereo vision system comprised of a pair of Dynamic Vision Sensors (left) which sends their output to a cluster of TrueNorth processors (right).