Abstract
In this paper, a new approach to real-time people segmentation through processing images captured by an infrared camera is introduced. The approach starts detecting human candidate blobs processed through traditional image thresholding techniques. Afterwards, the blobs are refined with the objective of validating the content of each blob. The question to be solved is if each blob contains one single human candidate or more than one. If the blob contains more than one possible human, the blob is divided to fit each new candidate in height and width.
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Castillo, J.C., Serrano-Cuerda, J., Fernández-Caballero, A. (2010). Robust People Segmentation by Static Infrared Surveillance Camera. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13022-9_35
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DOI: https://doi.org/10.1007/978-3-642-13022-9_35
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