Hyperspectral Object Tracking

Dear Colleagues,

Object tracking is an active research topic in computer vision, pattern recognition and remote sensing. We have witnessed significant progress on this topic over the past several years, with approaches moving from hand-crafted features to deep learning families. Nevertheless, tracking in grayscale or color videos has its intrinsic limitations in depicting physical properties of targets, especially reflectance of materials. It makes trackers vulnerable in complex scenarios with cluttered background and significant object shape changes. This problem can be effectively addressed by object tracking in hyperspectral videos which provide joint spectral, spatial, and temporal information, enabling computer vision system to perceive the materials of the objects besides the shape, texture, and semantic relationship of objects.

The Second Hyperspectral Object Tracking Challenge will be held with the 12th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). The goal of this contest is to boost the research on hyperspectral object tracking. This special issue provides a further opportunity to bring together the global research community actively involved in this field and highlights ongoing investigations and new applications of hyperspectral video data and tools in this filed.

The authors are not required to take part in the WHISPERS 2022 Hyperspectral Object Tracking Challenge. Articles may address but are not limited to the following topics:

• Hyperspectral Video Generation
• Hyperspectral Video Processing
• Hyperspectral Tracking
• Hyperspectral/Multispectral Object Detection
• Hyperspectral Snapshot Compressive Imaging
• Illumination Estimation

Dr. Fengchao Xiong
Dr. Jun Zhou
Prof. Dr. Yanfei Zhong
Dr. Pedram Ghamisi
Prof. Dr. Jocelyn Chanussot
Guest Editors

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