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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
