Worm Tracking Module.

<p>The tracking module associates detected targets across frames using Kalman filtering and the Hungarian algorithm, with additional logic to manage trajectory initiation and inactive states. Behavioral analysis is performed based on the resulting trajectories.</p>

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Bibliographic Details
Main Author:	Xiaoke Liu (11388323) (author)
Other Authors:	Jianming Liu (188385) (author), Wenjie Teng (5925236) (author), Yuzhong Peng (7329866) (author), Boao Li (13885143) (author), Xiaoqing Han (2531497) (author), Jing Huo (10129142) (author)
Published:	2025
Subjects:	Ecology Sociology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified unlike traditional labor intensive measurement approaches including locomotion velocity gene function research comparative evaluations demonstrate body bending angle various behavioral parameters multiple movement parameters including movement speed complex worm behaviors 5 %, recall maintaining automated extraction enhancing tracking continuity proposed enhanced c tracking </ p worm detection processing speed multiple worms behavioral data 7 %, 6 %, automated c automated approach automated analysis tracking results tracking accuracy precise tracking manually tracking xlink "> throughput method thereby laying significantly improving roll frequency robust foundation quantitative analysis locomotor behavior large numbers integrates yolov8 innovatively propose fps ). experimental throughput enabling real efficient tool drug screening deep learning crucial platform biological significance approach advances analyzing c
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Worm Tracking Module.

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