Abstract
In order to track the dim–small object in fast moving scenario, a precise tracking method based on the hyperspectral features is proposed since the traditional full color tracking seems impossible for unobvious color and contour features. A multi-dimensional feature space is extracted with the spectral fingerprint model. To track the dim–small object with high speed, this paper integrates a Kalman filter into the nonparametric kernel density estimator which is built with the probability histogram of spectral features. To avoid the object jump incident, a layered particle filter is introduced into spectral tracking algorithm. The experimental study and analysis show that the tracking algorithm based on the hyperspectral features is accurate, real-time and robust.
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Sheng, H., Ouyang, Y., Li, C. et al. Tracking Dim–Small Object Based on the Hyperspectral Features. Arab J Sci Eng 39, 1725–1736 (2014). https://doi.org/10.1007/s13369-013-0711-1
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DOI: https://doi.org/10.1007/s13369-013-0711-1