@inproceedings{Glavtchev:2011:FSL,
| title | = | "Feature-Based Speed Limit Sign Detection Using a Graphics Processing Unit", |
| booktitle | = | "IEEE Intelligent Vehicles", |
| author | = | "Vladimir
Glavtchev AND Pinar
Muyan-Ozcelik AND Jeffrey
M. Ota AND John
D. Owens ", |
| year | = | "2011", |
| month | = | jun, |
| keywords | = | "intelligent vehicles, feature-based, speed limit recognition, GPGPU, GPU, parallel", |
| organization | = | "IEEE", |
| location | = | "Baden-Baden, Germany", |
| eventtime | = | "June 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.", |
