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Published Articles >> Table of Contents >> Abstract
17th International Conference on Pattern Recognition (ICPR'04) - Volume 2
pp. 311-314
Evaluation of Model-Based Interactive Flower Recognition
Jie Zou, Rensselaer Polytechnic Institute, New York
George Nagy, Rensselaer Polytechnic Institute, New York
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334185
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| Abstract |
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We introduce the concept of Computer Assisted Visual InterActive Recognition (CAVIAR). In CAVIAR, a parameterized geometrical model serves as the human-computer communication channel. We implemented a flower recognition system and evaluated it on 30 inexperienced subjects. Major conclusions include: 1) the accuracy of the CAVIAR system is much higher than that of the machine alone; 2) its recognition time is much lower than that of the human alone; 3) it can be initialized with as few as one training sample per class and still achieve high accuracy; 4) it demonstrates a self-learning ability, which suggests that instead of initializing the CAVIAR system with many training samples, we can trust the system's self-learning ability.
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 Additional Information
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Citation:
Jie Zou, George Nagy,
"Evaluation of Model-Based Interactive Flower Recognition,"
icpr,
pp. 311-314,
17th International Conference on Pattern Recognition (ICPR'04) - Volume 2,
2004
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