11 July 2019 Evaluation of detection and tracking performance in imaging systems
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Abstract
Imaging systems can be used to obtain situational awareness in maritime situations. Important tools for these systems are automatic detection and tracking of objects in the acquired imagery, in which numerous methods are being developed. When designing a detection or tracking algorithm, its quality should be ensured by a comparison with existing algorithms and/or with a ground truth. Detection and tracking methods are often designed for a specific task, so evaluation with respect to this task is crucial, which demands for different evaluation measures for different tasks. We, therefore, propose a variety of quantitative measures for the performance evaluation of detectors and trackers for a variety of tasks. The proposed measures are a rich set from which an algorithm designer can choose in order to optimally design and assess a detection or tracking algorithm for a specific task. We compare these different evaluation measures by using them to assess detection and tracking quality in different maritime detection and tracking situations, obtained from three real-life infrared video data sets. With the proposed set of evaluation measures, a user is able to quantitatively assess the performance of a detector or tracker, which enables an optimal design for his approach.
© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2019/$28.00 © 2019 SPIE
Wyke Huizinga, Annegreet Van Opbroek, Raimon H. R. Pruim, Richard J. M. den Hollander, Sebastiaan P. van den Broek, Emma S. Schook, Klamer Schutte, Nanda van der Stap, and Judith Dijk "Evaluation of detection and tracking performance in imaging systems," Optical Engineering 58(7), 073103 (11 July 2019). https://doi.org/10.1117/1.OE.58.7.073103
Received: 23 April 2019; Accepted: 18 June 2019; Published: 11 July 2019
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Imaging systems

Video

Surveillance

Detection and tracking algorithms

Sensors

Optical engineering

Target detection

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