Abstract
Object tracking is an important topic in computer vision and image recognition. The probabilistic approach using the particle filter has been recently used for the tracking of moving objects. Based on our trajectory recording system of the soccer scene with multiple video cameras at one view point, we propose the extended approach to increase the tracking robustness and accuracy using the particle filter. The proposed approach makes it possible to pass the necessary particle information using the color histogram and other key factors from one image to the next image, which are taken through the different camera scene with one PC. The performance of the proposed approach is evaluated in the experiments with real video sequence. It is shown that one PC can handle two video images in real-time.
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Iwahori, Y., Takai, T., Kawanaka, H., Itoh, H., Adachi, Y. (2006). Particle Filter Based Tracking of Moving Object from Image Sequence. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_52
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DOI: https://doi.org/10.1007/11893004_52
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