TitleFeature-Based Speed Limit Sign Detection Using a Graphics Processing Unit (In Proceedings)
inIEEE Intelligent Vehicles
Author(s) Vladimir Glavtchev, Pinar Muyan-Ozcelik, Jeffrey M. Ota, John D. Owens
Keyword(s)intelligent vehicles, feature-based, speed limit recognition, GPGPU, GPU, parallel
Year June 2011
LocationBaden-Baden, Germany
DateJune 5-9, 2011
Abstract In this study we test the idea of using a graphics processing unit (GPU) as an embedded co-processor for realtime detection of European Union (EU) speed-limit signs. The input to the system is a set of grayscale videos recorded from a forward-facing camera mounted in a vehicle. We introduce a new technique for implementing the radial symmetry detector (RSD) efficiently using the native rendering capabilities of a GPU. The technique maps the algorithms to the hardware such that the detection of speed-limit sign candidates is significantly accelerated. The system reaches up to 88% detection rate and runs at 33 frames per second on video sequences with VGA (640x480) resolution on an embedded system with an Intel Atom 230 @ 1.67 GHz CPU and a NVIDIA GeForce 9400M GS GPU.