Fifth IEEE International Workshop on Computer Architectures for Machine Perception (CAMP'00)
Space Variant Vision and Pipelined Architecture for Time to Impact Computation
Padova, Italy
September 11-September 13
ISBN: 0-7695-0740-9
F. Pardo, Dept. de Inf., Valencia Univ., Spain
F. Mico, Dept. de Inf., Valencia Univ., Spain
Image analysis is one of the most interesting ways for a mobile vehicle to understand its environment. One of the tasks of an autonomous vehicle is to get accurate information of what it has in front, to avoid collision or find a way to a target. This task requires real-time restrictions depending on the vehicle speed and external object movement. The use of normal cameras, with homogeneous (squared) pixel distribution, for real-time image processing, usually requires high performance computing and high image rates. A different approach makes use of a CMOS space-variant camera that yields a high frame rate with low data bandwidth. The camera also performs the log-polar transform, simplifying some image processing algorithms. One of this simplified algorithms is the time to impact computation. The calculation of the time to impact uses a differential algorithm. A pipelined architecture specially suited for differential image processing algorithms has been also developed using programmable FPGAs.
Index Terms:
pipeline processing; pipelined architecture; time to impact computation; autonomous vehicle; avoid collision; real-time image processing; space-variant camera; image processing; differential image processing
Citation:
F. Pardo, I. Llorens, F. Mico, J.A. Boluda, "Space Variant Vision and Pipelined Architecture for Time to Impact Computation," camp, pp.122, Fifth IEEE International Workshop on Computer Architectures for Machine Perception (CAMP'00), 2000