Abstract
The tropical cyclone is one of disaster weather that cause serious damages for human community. It is necessary to forecast the tropical cyclone efficiently and accurately for reducing the loss caused by tropical cyclones. With the development of computer vision and satellite technology, high quality meteorological data can be got and advanced technologies have been proposed in visual tracking domain. This makes it possible to develop algorithms to do the automatic tropical cyclone tracking which plays a critical role in tropical cyclone forecast. In this paper, we present a novel database for Typical Cyclone Tracking based on Satellite Cloud Image, called TCTSCI. To the best of our knowledge, TCTSCI is the first satellite cloud image database of tropical cyclone tracking. It consists of 28 video sequences and totally 3,432 frames with \(6001\times 6001\) pixels. It includes tropical cyclones of five different intensities distributing in 2019. Each frame is scientifically inspected and labeled with the authoritative tropical cyclone data. Besides, to encourage and facilitate research of multimodal methods for tropical cyclone tracking, TCTSCI provides not only visual bounding box annotations but multimodal meteorological data of tropical cyclones. We evaluate 11 state-of-the-art and widely used trackers by using OPE and EAO metrics and analyze the challenges on TCTSCI for these trackers.
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Acknowledgments
This work is partially supported by National Key Research and Development Program of China (No. 2018YFE0126100), National Natural Science Foundation of China under Grant (No. 61906168, 61976192, 41775008 and 61702275).
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Huang, C., Chan, S., Bai, C., Ding, W., Zhang, J. (2021). Tropical Cyclones Tracking Based on Satellite Cloud Images: Database and Comprehensive Study. In: Lokoč, J., et al. MultiMedia Modeling. MMM 2021. Lecture Notes in Computer Science(), vol 12573. Springer, Cham. https://doi.org/10.1007/978-3-030-67835-7_2
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