Research on the multitarget 3D trajectory tracking method of Thalassodes immissaria in the thermal infrared region based on YOLOX-GMM and SORT-Pest
Year: 2024
Type: article
Abstract: Introduction Studying the behavioral responses and movement trajectories of insects under different stimuli is crucial for developing more effective biological control measures. Therefore, accurately obtaining the movement trajectories and behavioral parameters of insects in three-dimensional space is essential. Methods This study used the litchi pest Thalassodes immissaria as the research object. A special binocular vision observation system was designed for nighttime movement. A thermal infrared camera was used for video recording of T. immissaria in a lightless environment. Moreover, a multi-object tracking method based on the YOLOX-GMM and SORT-Pest algorithms was proposed for tracking T. immissaria in thermal infrared images. By obtaining the central coordinates of the two T. immissaria in the video, target matching and 3D trajectory reconstruction in the parallel binocular system were achieved. Results Error analysis of the T. immissaria detection and tracking model, as well as the 3D reconstruction model, showed that the average accuracy of T. immissaria detection reached 89.6%, tracking accuracy was 96.9%, and the average error of the reconstructed 3D spatial coordinates was 15 mm. Discussion These results indicate that the method can accurately obtain the 3D trajectory and motion parameters of T. immissaria. Such data can greatly contribute to researchers' comprehensive understanding of insect behavioral patterns and habits, providing important support for more targeted control strategies.
Source: Frontiers in Plant Science
Authors: Xinrui Qiu, Juan Xia, Ye Zeng, Guangwen Huang, Bolai Xin, Runpeng Jiang, Kaixuan Wu, Zhe Ma, Jun Li
Institution: South China Agricultural University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,295
Awards: G3515417775, G4213545139
OpenAlex ID: W4403202032
