4.7 Article

Object Tracking in Satellite Videos: A Spatial-Temporal Regularized Correlation Filter Tracking Method With Interacting Multiple Model

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出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2022.3179770

关键词

Target tracking; Correlation; Videos; Satellites; Object tracking; Kalman filters; Predictive models; Correlation filter; interacting multiple model (IMM); object tracking; satellite videos

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In this article, a novel correlation filter algorithm combined with an interacting multiple model (IMM) for object tracking in satellite videos is proposed. This tracker shows good robustness to occlusion and achieves excellent performance compared to other state-of-the-art methods.
Target occlusion is common in satellite videos, which makes object tracking difficult because most state-of-the-art trackers are not robust to occlusion, particularly complete occlusion. In this letter, we propose a novel correlation filter algorithm with an interacting multiple model (IMM) for object tracking in satellite videos that combines the strength of the correlation filter and the IMM. When the target is occluded, we utilize the IMM to predict target position. Therefore, the proposed tracker is robust to occlusion. The experimental results demonstrate that our tracker performs favorably when the target is occluded and achieves excellent performance compared with state-of-the-art methods.

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