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UAS-based object tracking via Deep Learning | IEEE Conference Publication | IEEE Xplore

UAS-based object tracking via Deep Learning


Abstract:

Unmanned Aerial System-based object tracking is a challenging new task in the computer vision community. In addition, existing benchmark and research focus on short seque...Show More

Abstract:

Unmanned Aerial System-based object tracking is a challenging new task in the computer vision community. In addition, existing benchmark and research focus on short sequences that are less than a minute long. In this work, we show the limitations of state-of-the art trackers in front of long-term aerial tracking. We propose a novel long-term, real-time, intelligent system for unmanned aerial system -based vehicle tracking utilizing deep learning techniques. We integrate a fast and accurate correlation filter with the expressiveness of a convolutional neural network embedding. A re-initialization policy based on a real-time anomaly detection on correlation map combined with a one-shot detector ensure that our system is impervious to drift and occlusion.
Date of Conference: 07-09 January 2019
Date Added to IEEE Xplore: 14 March 2019
ISBN Information:
Conference Location: Las Vegas, NV, USA

References

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