Title :
Interactive visual pattern recognition
Author :
Nagy, George ; Zou, Jie
Author_Institution :
Dept. of Electr. Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
Abstract :
Computer Assisted Visual Interactive Recognition (CAVIAR) draws on sequential pattern recognition, image database, expert systems, pen computing, and digital camera technology. It is designed to recognize wildflowers and other families of similar objects more accurately than machine vision and faster than most laypersons. The novelty of the approach is that human perceptual ability is exploited through interaction with the image of the unknown object. The computer remembers the characteristics of all previously seen classes, suggests possible operator actions, and displays confidence scores based on already detected features. In one application, consisting of 80 test images of wildflowers, 10 laypersons averaged 80% recognition accuracy at 12 seconds per flower.
Keywords :
computer vision; expert systems; pattern recognition; visual databases; computer assisted visual interactive recognition; digital camera technology; expert systems; human perceptual ability; image database; interactive visual pattern recognition; machine vision; pen computing; sequential pattern recognition; Application software; Computer displays; Computer vision; Digital cameras; Expert systems; Humans; Image databases; Image recognition; Machine vision; Pattern recognition;
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
Print_ISBN :
0-7695-1695-X
DOI :
10.1109/ICPR.2002.1048342