3D zebrafish tracking with topology association. Issue 4 (23rd November 2022)

• Record Type: Journal Article
• Authors: Xu, Yuan; Jin, Yichao; Zhang, Yang; Zhu, Qunxiong; He, Yanlin; Sheng, Hao
• Is Part Of: IET image processing. Volume 17:Issue 4(2023)
• Page Start: 1044
• Page End: 1059
• Publication Date: 2022-11-23
• Subjects: Multi‐object tracking -- topology association -- 3D tracking -- Zebrafish; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/ipr2.12694
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract: Recently, zebrafish has received more and more attention due to its wide range of applications such as regeneration promoting therapeutics and drug discovery. Therefore, vision‐based trackers are utilized to record the swimming trajectory of zebrafish. In this paper, a re‐association method is introduced in the 3D reconstruction process to generate missed targets caused by occlusion. Since the variation of the overall tracking targets has the property of continuity and stability, a topology association model (TAM) is proposed by point group similarity into the tracking framework. TAM describes the movement of zebrafish from the macroscopic level and utilizes the changes of the point group structure for tracking. Experimental results show that the tracking framework enhances the overall performance and promotes the trajectory integrity. On the latest 3D‐ZeF20 benchmark, state‐of‐the‐art results are achieved. In addition, TAM tracking framework is applied to 2D general tracking to prove that the method is useful and have great advantage in other scenarios with relatively stable amount of targets as well. Abstract : An innovative method to track zebrafish in 3D and achieve outstanding performance. This method also remarkably tracks general targets when the number is stable, such as human behaviors in a basketball game.