The large scene video text dataset for scene video text spotting (LSVTD)

Research Tasks

Video Text Tracking

2021-06-01 (v. 1)

Contact author

Baorui Zou

Hikvision Research Institute

18210240270@fudan.edu.cn

(+86) 18826072052


This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

Description

TASK 2 - Video Text Tracking

This task intends to track all the text streams in videos. 

Protocol

We evaluate results based on an adaptation of the CLEAR-MOT [1] and VACE [2] evaluation framework. We here adapt these metrics to the specificities of text tracking by following the protocals in [3], i.e., MOTA, MOTP, ATA will be used as the evaluation metrics. 

 

 

References

[1]. K. Bernardin and R. Stiefelhagen, “Evaluating multiple object tracking performance: The CLEAR MOT metrics,” EURASIP Journal on Image and Video Processing, vol. 2008, May 2008.

[2]. R. Kasturi, D. Goldgof, P. Soundararajan, V. Manohar, J. Garofolo, R. Bowers, M. Boonstra, V. Korzhova, and J. Zhang, “Framework for performance evaluation of face, text, and vehicle detection and tracking in video: Data, metrics, and protocol,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 2, pp. 319–336, 2009.

[3]. Dimosthenis Karatzas, Faisal Shafait, Seiichi Uchida, Masakazu Iwamura, Lluis Gomez i Bigorda, Sergi Robles Mestre, Joan Mas, David Fernandez Mota, Jon Almazan Almazan, and Lluis Pere De Las Heras. 2013. ICDAR 2013 robust reading competition. In ICDAR. 1484–1493.

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