Paper
3 April 2024 StereoYolo+DeepSORT: a framework to track fish from underwater stereo camera in situ
Aya Saad, Stian Jakobsen, Morten Bondø, Mats Mulelid, Eleni Kelasidi
Author Affiliations +
Proceedings Volume 13072, Sixteenth International Conference on Machine Vision (ICMV 2023); 1307213 (2024) https://doi.org/10.1117/12.3023414
Event: Sixteenth International Conference on Machine Vision (ICMV 2023), 2023, Yerevan, Armenia
Abstract
This paper presents a 3D multiple object detection and tracking framework for identifying and quantifying changes in fish behaviour through tracking the 3D position, distance and speed of fish with respect to an underwater stereo camera. The framework consists of six essential modules based on 3D object detection to identify fish and multiple object tracking algorithms to track the fish in sequential frames. In particular, the latest version of Yolo (Yolov7) is utilised for object detection and the deep SORT algorithm is used for multiple object tracking. The framework was tested using videos captured from an underwater stereo camera in an industrial-scale sea-based fish farm. The results showed that the framework was able to accurately detect and track multiple fish in 3D. The fish position, distance and speed relative to the camera were also successfully detected. The results of this study demonstrate the effectiveness of this framework in identifying and quantifying changes in fish behaviour. The proposed novel framework has the potential to greatly enhance our understanding of fish behaviour in their natural habitats, leading to new insights into fish ecology and behaviour, while at the same time, it can enable researchers to study fish behaviour in a more detailed and accurate way.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Aya Saad, Stian Jakobsen, Morten Bondø, Mats Mulelid, and Eleni Kelasidi "StereoYolo+DeepSORT: a framework to track fish from underwater stereo camera in situ", Proc. SPIE 13072, Sixteenth International Conference on Machine Vision (ICMV 2023), 1307213 (3 April 2024); https://doi.org/10.1117/12.3023414
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KEYWORDS
Object detection

3D tracking

Cameras

Stereoscopic cameras

Detection and tracking algorithms

Video

Calibration

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