A new tracking method for small infrared targets

Authors:
Lei Yang;Weiping Lu;Jie Yang
Affiliations:
Physics Department, EPS, Heriot-Watt University, Edinburgh, UK;Physics Department, EPS, Heriot-Watt University, Edinburgh, UK;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, P. R. China
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 3
Cited 0

Kernel-Based Object Tracking

IEEE Transactions on Pattern Analysis and Machine Intelligence
The Gaussian Mixture Probability Hypothesis Density Filter

IEEE Transactions on Signal Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.02

Visualization

Abstract

We report on a new approach to tracking small infrared targets. The method improves on existing target trackers by combining mean-shift tracker with Kalman filtering and by updating the tracking parameters through the measurement of the complexity of the target region. We have further developed a nonlinear algorithm to improve the robustness of the traditional mean-shift tracker for small infrared targets. Experimental results demonstrate a superior performance of our method compared to existing target trackers, particularly in the environment of strong measurement noise and large variation of illumination.