@mastersthesis{Glavtchev:2009:ESS,
| title | = | "EU Speed-limit Sign Detection Using a Graphics Processing Unit", |
| author | = | "Vladimir
Glavtchev ", |
| year | = | "2009", |
| month | = | dec, |
| keywords | = | "GPGPU, GPU, speed limit recognition, intelligent vehicles, feature-based", |
| school | = | "Electrical and Computer Engineering, University of California, Davis", |
| abstract | = | "In this study we test the idea of using a graphics processing unit (GPU) as an em-
bedded co-processor for real-time speed-limit sign detection. We implement a sys-
tem that operates in real-time within the computational limits of contemporary em-
bedded general-purpose processors. The input to the system is a set of grayscale
videos recorded from a camera mounted in a vehicle. We implement a new tech-
nique to realize the radial symmetry transform e±ciently using rendering primi-
tives accelerated by graphics hardware to detect the location of speed-limit sign
candidates. 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 and a Nvidia GeForce 9200M GS.", |
