Real-Time Tracking in Satellite Videos via Joint Discrimination and Pose Estimation

Abstract

<p><strong>Abstract.</strong> Object tracking has gained much attention in the field of computer vision and intelligent traffic analysis. Satellite videos are more suitable for long-distance tracking comparing to the road traffic videos. However, most of the state-of-the-art methods produce poor results when applied to satellite videos, due to low resolution of the small target and interference from similar background in satellite videos. In this paper, we present an improved Discriminative Correlation Filter based approach specifically tailored for small objects tracking in satellite videos through applying spatial weight in the filter and estimating the pose by Kalman filter. First, a spatial mask is introduced to encourage the final filter to give different contributions depending on the spatial distance. Furthermore, Kalman filter is incorporated into the approach with the aim of predicting the position when the target run into the large area similar background region. Finally, an efficient strategy for combining the improved DCF tracker and pose estimation is proposed. Experimental results on three satellite videos describing the traffic conditions of three cities demonstrate that the proposed approach can effectively track the targets even though the targets are similar to the background region in a period of time. Compare with other state-of-the-art methods, the final accuracies and speeds of our method achieve the best.</p>

Object Tracking Based on Satellite Videos: A Literature Review

“…KCF + multi-frames [6] 2017 KCF with the three-frame-difference [44] 2022 KCF with Multi-feature fusion KCF + target motion [45] 2019 Improved discriminative CF for small objects tracking [46] 2019 High-speed CF-based tracker for object tracking [47] 2019 KCF embedded with motion estimations [48] 2021 Feature fusion, position compensation, local object region KCF + kernel adaptation [49] 2018 VCF using velocity feature and inertia mechanism [50] 2019 Hybrid KCF with histogram of oriented gradient [51] 2021 Rotation-adaptive CF [52] 2022 Rotation-adaptive CF with motion constraint [53] 2022 Spatial-Temporal regularized CF with interacting multiple model [54] 2022 Kernelized CF with color-name features In 2017, Ref. [6] presented a new object tracking method by taking advantage of the KCF and the three-frame-difference method to deal with satellite videos.…”

“…In 2019, Ref. [45] developed an improved discriminative CF for small object tracking in satellite videos. Instead of employing a change detection tracking model, the authors first proposed a spatial mask to promote the CF to give different contributions depending on the spatial distance.…”