High-Speed, Real-Time, Spike-Based Object Tracking and Path Prediction on Google Edge TPU
Jonah P. Sengupta, Rajkumar Kubendran, Emre Neftci, Andreas G. Andreou
Abstract
As computation and advanced high-dimensional signal processing is pushed to edge computational devices, energy efficient, unconventional architectures are needed to ameliorate this growing need. The Google Edge TPU, first used on a Cloud platform, is one such accelerator that is now commercially available for consumer use. Similarly, low-power, data-efficient vision sensors, such as the Dynamic Vision Sensor (DVS), have been developed and commercialized as well to improve upon the large data redundancy seen in these ML applications. This live demonstration is linking these two technologies to benchmark the Coral Edge TPU Board in a high-speed object tracking and prediction application. In comparison to a floating point architecture of similar form factor, the Intel Compute Stick, the Edge TPU has been show to outperform in terms of latency and computational efficiency.