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Performance Evaluation of Object Detection Algorithms
Quebec City, QC, Canada August 11-August 15
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.104819816th International Conference on Patt ...
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Vladimir Y. Mariano, Pennsylvania State University
Junghye Min, Pennsylvania State University
Jin-Hyeong Park, Pennsylvania State University
Rangachar Kasturi, Pennsylvania State University
David Mihalcik, University of Maryland at College Park
Huiping Li, University of Maryland at College Park
David Doermann, University of Maryland at College Park
Thomas Drayer, Department of Defense
The continuous development of object detection algorithms is ushering in the need for evaluation tools to quantify algorithm performance. In this paper, a set of seven metrics are proposed for quantifying different aspects of a detection algorithm? s performance. The strengths and weaknesses of these metrics are described. They are implemented in the Video Performance Evaluation Resource (ViPER) system and will be used to evaluate algorithms for detecting text, faces, moving people and vehicles. Results for running two previous text-detection algorithms on a common data set are presented.
Citation:
Vladimir Y. Mariano, Junghye Min, Jin-Hyeong Park, Rangachar Kasturi, David Mihalcik, Huiping Li, David Doermann, Thomas Drayer, "Performance Evaluation of Object Detection Algorithms," icpr, vol. 3, pp.30965, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 3, 2002
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