Simple online and real-time underwater multiple object tracking

Panpan Lu; Junyu Dong; Xin Sun

doi:10.1117/12.2589351

27 January 2021 Simple online and real-time underwater multiple object tracking

Panpan Lu, Junyu Dong, Xin Sun

Proceedings Volume 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020); 117200F (2021) https://doi.org/10.1117/12.2589351
Event: Twelfth International Conference on Graphics and Image Processing, 2020, Xi'an, China

Abstract

For underwater videos, the effects of object tracking becomes more challenging since videos taken are greatly influenced by blurry background, illumination condition and occlusion. Hence, this paper explores an effective approach for underwater multiple object tracking where the main advantage lies in associating objects effectively for online and real-time applications. It is a remarkable fact that detection quality is a key factor for tracking effects, where changing the detector improves the result of tracking. In the process, the whole model consists of detection, Kalman Filter and Hungarian Algorithm. While the detection method applied is yolov3 as it has an excellent performance in terms of speed and accuracy. Consequently, yolov3 can be perfectly embedded in the model. The model embraces an impressive tracking result on underwater dataset. Tracking results have been analyzed using Multiple Object Tracking Accuracy (MOTA) and Multiple Object Tracking Precision (MOTP).

Citation Download Citation

Panpan Lu, Junyu Dong, and Xin Sun "Simple online and real-time underwater multiple object tracking", Proc. SPIE 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020), 117200F (27 January 2021); https://doi.org/10.1117/12.2589351

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