Hy-Tracker: A Novel Framework for Enhancing Efficiency and Accuracy of Object Tracking in Hyperspectral Videos

TL;DR

Hy-Tracker is a new framework that combines YOLOv7 detection with a refined tracking module and Kalman filter to improve object tracking accuracy and efficiency in hyperspectral videos, addressing occlusion and scale variation challenges.

Contribution

This paper introduces Hy-Tracker, the first to integrate YOLOv7 with a specialized tracking module and Kalman filter for hyperspectral video object tracking, filling a gap in current methods.

Findings

Hy-Tracker outperforms existing methods on hyperspectral benchmarks.

Incorporating Kalman filter improves robustness to occlusion.

Refined tracking enhances accuracy over YOLOv7 alone.

Abstract

Hyperspectral object tracking has recently emerged as a topic of great interest in the remote sensing community. The hyperspectral image, with its many bands, provides a rich source of material information of an object that can be effectively used for object tracking. While most hyperspectral trackers are based on detection-based techniques, no one has yet attempted to employ YOLO for detecting and tracking the object. This is due to the presence of multiple spectral bands, the scarcity of annotated hyperspectral videos, and YOLO's performance limitation in managing occlusions, and distinguishing object in cluttered backgrounds. Therefore, in this paper, we propose a novel framework called Hy-Tracker, which aims to bridge the gap between hyperspectral data and state-of-the-art object detection methods to leverage the strengths of YOLOv7 for object tracking in hyperspectral videos. Hy-Tracker not only introduces YOLOv7 but also innovatively incorporates a refined tracking module on top of YOLOv7. The tracker refines the initial detections produced by YOLOv7, leading to improved object-tracking performance. Furthermore, we incorporate Kalman-Filter into the tracker, which addresses the challenges posed by scale variation and occlusion. The experimental results on hyperspectral benchmark datasets demonstrate the effectiveness of Hy-Tracker in accurately tracking objects across frames.