Abstract
This paper discusses arithmetic of inversible neural network. Condensation algorithm is based on the sampling factor for conditional density propagation method, combined with the dynamic model of learning, can complete robust motion tracking. This technology was first widely used in military guidance, introduced into the monitoring system, tracking objects in particular to people or other relatively slow speed of the target, thus tracking method is more simple than the former. Current tracking methods can generally be divided into match tracking and motion tracking. Based on match of track algorithm main has regional match track, and profile match track and the features match track, regional match track of basic thought is put advance extraction of movement regional as match template, set a match metric, and in stay match figure as move template search target. Although the amount of calculation is decreased, but cannot solve the inherent defects profiles matching the basic idea is to extract the contour of objects and to track profile properties. Region matching pursuit algorithm by contour matching benefits can be achieved at a very good match, and the complexity is not high, is a focus of current research.
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Jian, C., Gang, L., Sen, Z., Cong, Y. (2018). Image Fusion Study by Inversible System of Neural Network. In: Qiao, F., Patnaik, S., Wang, J. (eds) Recent Developments in Mechatronics and Intelligent Robotics. ICMIR 2017. Advances in Intelligent Systems and Computing, vol 691. Springer, Cham. https://doi.org/10.1007/978-3-319-70990-1_68
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DOI: https://doi.org/10.1007/978-3-319-70990-1_68
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