Intel Demonstration of Scalable Deep Learning-based Face Detection and Recognition with FPGAs

Richard Chuang, Global Platform Solutions Architect at Intel, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Chuang demonstrates an end-to-end face detection and recognition reference solution using the OpenVINO toolkit. Four primary algorithms are running in this demo system on top of OpenVINO: face detection, landmark detection, feature extraction, and face matching. The Core i7 system supports 500 fps/core running face detection and landmark detection, the Core i5 plus Arria 10 FPGA combination system is able to deliver 120 fps on a face feature extraction algorithm, and the Xeon SP Platinum server, Optane disk and IMDT are together able to find a specific face among 20 million candidate faces in 20 ms.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



1646 N. California Blvd.,
Suite 360
Walnut Creek, CA 94596 USA

Phone: +1 (925) 954-1411
Scroll to Top