Real-time Performance Evaluation Metrics for Object Detection and Tracking of Intelligent Video Surveillance Systems

نویسندگان

  • Kyoung Yeon Kim
  • Jaehyun Park
چکیده

This paper proposes real-time performance evaluation metrics for the object detection and tracking algorithms used in intelligent video surveillance systems. Since an intelligent video surveillance system should support real-time performance, as well as the spatial accuracy of the object detection and tracking, the performance evaluation tool should evaluate not only the spatial accuracy, but also the real-time property. In this paper, a total of eight performance evaluation metrics for the real-time object detection and tracking system have been proposed. The proposed metrics have been designed by combining the degree of precision of the detected objects, the ratio of the incorrectly detected objects, and real-time performance of the algorithm.

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تاریخ انتشار 2016