Using Stereo Vision and Fuzzy Systems for Detecting and Tracking People Paúl, Rui Aguirre Molina, Eugenio García Silvente, Miguel Muñoz Salinas, Rafael People Tracking Stereo Vision Fuzzy systems Particle Filtering Color Information This paper describes a system capable of detecting and tracking various people using a new approach based on stereo vision and fuzzy logic. First, in the people detection phase, two fuzzy systems are used to assure that faces detected by the OpenCV face detector actually correspond to people. Then, in the tracking phase, a set of hierarchical fuzzy systems fuse depth and color information captured by a stereo camera assigning different confidence levels to each of these information sources. To carry out the tracking, several particles are generated while fuzzy systems compute the possibility that some generated particle corresponds to the new position of people. The system was tested and achieved interesting results in several situations in the real world. 2023-12-22T07:47:13Z 2023-12-22T07:47:13Z 2010 conference output Paúl, R., Aguirre, E., García-Silvente, M., Muñoz-Salinas, R. (2010). Using Stereo Vision and Fuzzy Systems for Detecting and Tracking People. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2010. Communications in Computer and Information Science, vol 81. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14058-7_60 https://link.springer.com/chapter/10.1007/978-3-642-14058-7_60 https://hdl.handle.net/10481/86424 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Springer