Paper Info
Title
Space Variant Vision and Pipelined Architecture for Time to Impact Computation
Abstract
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.
Year
DOI
Venue
2000
10.1109/CAMP.2000.875967
CAMP
Keywords
Field
DocType
impact computation,high image rate,real-time image processing,mobile vehicle,differential image processing algorithm,space variant vision,high performance computing,autonomous vehicle,image processing algorithm,pipelined architecture,vehicle speed,image analysis,high frame rate,remotely operated vehicles,bandwidth,computer architecture,computer vision,real time,image processing,mobile robots,pixel
Remotely operated underwater vehicle,Computer vision,Computer science,Image processing,Field-programmable gate array,Bandwidth (signal processing),Frame rate,Pixel,Artificial intelligence,Digital image processing,Computation
Conference
ISBN
Citations 
PageRank 
0-7695-0740-9
2
0.39
References 
Authors
5
4
Name
Order
Citations
PageRank
F. Pardo18211.00
I. Llorens220.39
F. Mico320.39
J. A. Boluda420.39