Grayscale-Thermal Object Tracking (GTOT) Benchmark

Description

We collected 50 grayscale-thermal video clips under different scenarios and conditions, e.g., office areas, public roads, and water pool, etc. Each grayscale video is paired with one thermal video. We manually annotated them with ground truth bounding boxes. All annotations are done by a full-time annotator, to guarantee consistency.

Citation

Chenglong Li, Hui Cheng, Shiyi Hu, Xiaobai Liu, Jin Tang, and Liang Lin, “Learning Collaborative Sparse Representation for Grayscale-Thermal Tracking”, IEEE Transactions on Image Processing, 2016.

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