Framework for Performance Evaluation of Face, Text, and Vehicle Detection and Tracking in Video: Data, Metrics, and Protocol

@article{Kasturi2009FrameworkFP,
  title={Framework for Performance Evaluation of Face, Text, and Vehicle Detection and Tracking in Video: Data, Metrics, and Protocol},
  author={Rangachar Kasturi and Dmitry B. Goldgof and Padmanabhan Soundararajan and Vasant Manohar and John S. Garofolo and Rachel Bowers and Matthew Boonstra and Valentina N. Korzhova and Jing Zhang},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2009},
  volume={31},
  pages={319-336}
}
Common benchmark data sets, standardized performance metrics, and baseline algorithms have demonstrated considerable impact on research and development in a variety of application domains. These resources provide both consumers and developers of technology with a common framework to objectively compare the performance of different algorithms and algorithmic improvements. In this paper, we present such a framework for evaluating object detection and tracking in video: specifically for face, text… CONTINUE READING
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