Abstract
The mean-shift algorithm is an efficient technique for tracking 2D blobs through an image. Although it is important to adapt the mean-shift kernel to handle changes in illumination for robot vision at outdoor site, there is presently no clean mechanism for doing this. This paper presents a novel approach for color tracking that is robust to illumination changes for robot vision. We use two interleaved mean-shift procedures to track the spatial location and illumination intensity of a blob in an image. We demonstrate that our method enables efficient real-time tracking of the multiple color blobs against changes in illumination, where the illuminace ranges from 58 to 1,300 lx.
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Hayashi, Y., Fujiyoshi, H. (2008). Mean-Shift-Based Color Tracking in Illuminance Change. In: Visser, U., Ribeiro, F., Ohashi, T., Dellaert, F. (eds) RoboCup 2007: Robot Soccer World Cup XI. RoboCup 2007. Lecture Notes in Computer Science(), vol 5001. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68847-1_29
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DOI: https://doi.org/10.1007/978-3-540-68847-1_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68846-4
Online ISBN: 978-3-540-68847-1
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