FRHT dataset is established for studying full 360-degree out-of-plane rotation head single tracking. Overall, this dataset contains 50 sequences with 28,247 annotated bounding boxes of frames and expresses the diverse head movements in real-world conditions. FRHT is captured from Internet with a wide variety of scenes (e.g. street, sea, gymnasium, stage, grassland, ice rink) and activities (e.g. running, cycling, surfing, dancing, skating, flying). Naturally, it covers the most challenges of visual tracking problem annotated.
2. Data organization
Full sequences are collected from real-world videos in the public video websites (YouTube, Instagram, Meipai). The addresses of YouTube sources are contained in the dataset package.
In the package, each sequence with the certain scenario is an identified folder as activity_name + id_number.
The FRHT dataset is annotated using the following rules.
(1) All head poses from the front to the back are annotated; (2) For the front, the bounding box goes vertically from the chin to the forehead, and horizontally from one ear to the other or the nose depending on the pose; (3) For the backend, the bottom line of the bounding box is demarcated at the top of the neck; (4) Particularly, in the case that the ear and neck are not completely visible due to occlusion, we determine the bounding box according to the relative position of the eyes or shoulders.
Each row in the ground-truth files represents the bounding box of the target in that frame, (x, y, box-width, box-height).
Bingping Ma (email@example.com), Institute of Computing Technology, Chinese Academy of Sciences
Yulin Li (firstname.lastname@example.org), Institute of Computing Technology, Chinese Academy of Sciences
This dataset provided is published under the GNU General Public License 3.0. This means that you must attribute the work in the manner specified by the authors, you may not use this work for commercial purposes and if you alter, transform, or build upon this work, you may distribute the resulting work only under the same license. If you are interested in commercial usage you can contact us for further options.
Before using the dataset, you are recommended to refer to the
Yulin Li, Bingping Ma, Hong Chang, Xilin Chen. A Benchmark for Full Rotation Head Tracking. International Conference on Pattern Recognition (ICPR), 2018.
No matter where we infringe your rights, please tell us and we would modify the dataset without delay.