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Performance evaluation of object detection algorithms

  • Vladimir Y. Mariano
  • , Junghye Min
  • , Jin Hyeong Park
  • , Rangachar Kasturi
  • , David Mihalcik
  • , Huiping Li
  • , David Doermann
  • , Thomas Drayer
  • Pennsylvania State University
  • University of Maryland, College Park
  • Department of Defense

Research output: Contribution to journalArticlepeer-review

124 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)965-969
Number of pages5
JournalProceedings - International Conference on Pattern Recognition
Volume16
Issue number3
StatePublished - 2002

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