Abstract
In this paper we evaluate the performance of scene detection techniques, starting from the classic precision/recall approach, moving to the better designed coverage/overflow measures, and finally proposing an improved metric, in order to solve frequently observed cases in which the numeric interpretation is different from the expected results. Numerical evaluation is performed on two recent proposals for automatic scene detection, and comparing them with a simple but effective novel approach. Experimental results are conducted to show how different measures may lead to different interpretations.
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Acknowledgments
This work was carried out within the project “Città educante” (CTN01_00034_393801) of the National Technological Cluster on Smart Communities co funded by the Italian Ministry of Education, University and Research - MIUR.
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Baraldi, L., Grana, C., Cucchiara, R. (2015). Measuring Scene Detection Performance. In: Paredes, R., Cardoso, J., Pardo, X. (eds) Pattern Recognition and Image Analysis. IbPRIA 2015. Lecture Notes in Computer Science(), vol 9117. Springer, Cham. https://doi.org/10.1007/978-3-319-19390-8_45
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DOI: https://doi.org/10.1007/978-3-319-19390-8_45
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