Title :
Fast and accurate vision-based pattern detection and identification
Author :
Bruce, James ; Veloso, Manuela
Author_Institution :
Dept. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
Fast pattern detection and identification is fundamental problem for many applications of real-time vision systems. The desirable characteristics for a solution are that it requires little computation, localizes a pattern robustly and with high accuracy, and can identify a large number of unique pattern identifiers so that many of these markers can be tracked within a field a view. We will present a system that can accurately track a broad class of patterns both accurately and quickly, when used with a suitable low level vision system that can return calibrated coordinates of regions in an image. Both pattern design and the detection algorithm are considered together to find a solution meeting the above criteria. Along the way, assumptions are verified to make informed choices without relying on guesswork, and allowing similar system to be designed on a solid experimental and statistical basis.
Keywords :
computer vision; edge detection; object recognition; real-time systems; robot vision; detection algorithm; low level vision system; pattern identification; pattern identifiers; real-time vision systems; vision-based pattern detection; Algorithm design and analysis; Application software; Cameras; Computer science; Detection algorithms; Machine vision; Object detection; Robot vision systems; Robustness; Solids;
Conference_Titel :
Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on
Print_ISBN :
0-7803-7736-2
DOI :
10.1109/ROBOT.2003.1241768