Abstract
Pedestrian tracking video-based systems present particular problems such as the multi fragmentation or low level of compactness of the resultant blobs due to the human shape or movements. This paper shows how to improve the segmentation stage of a video surveillance system by adding morphological post-processing operations so that the subsequent blocks increase their performance. The adjustment of the parameters that regulate the new morphological processes is tuned by means of Evolution Strategies. Finally, the paper proposes a group of metrics to assess the global performance of the surveillance system. After the evaluation over a high number of video sequences, the results show that the shape of the tracks match up more accurately with the parts of interests. Thus, the improvement of segmentation stage facilitates the subsequent stages so that global performance of the surveillance system increases.
Funded by CICYT (TIC2002-04491-C02-02).
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Pérez, O., Patricio, M.Á., García, J., Molina, J.M. (2006). Improving the Segmentation Stage of a Pedestrian Tracking Video-Based System by Means of Evolution Strategies. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_39
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DOI: https://doi.org/10.1007/11732242_39
Publisher Name: Springer, Berlin, Heidelberg
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