Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8526, Japan
Yahoo Japan Corporation, Tokyo 102-8282, Japan.
J Exp Biol. 2018 Aug 24;221(Pt 16):jeb182469. doi: 10.1242/jeb.182469.
Image-based tracking software are regarded as valuable tools in collective animal behaviour studies. For such operations, image preprocessing is a prerequisite, and the users are required to build an appropriate image-processing pipeline for extracting the shape of animals. Even if the users successfully design an image-processing pipeline, unexpected noise in the video frame may significantly reduce the tracking accuracy in the tracking step. To address these issues, we propose UMATracker (Useful Multiple Animal Tracker), which supports flexible image preprocessing by visual programming, multiple tracking algorithms and a manual tracking error-correction system. UMATracker employs a visual programming user interface, wherein the user can intuitively design an image-processing pipeline. Moreover, the software also enables the user to visualize the effect of image processing. We implement four different tracking algorithms to enable the users to choose the most suitable algorithm. In addition, UMATracker provides a manual correction tool for identifying and correcting tracking errors.
基于图像的跟踪软件被认为是集体动物行为研究中的有价值的工具。对于此类操作,图像预处理是前提,用户需要构建适当的图像处理管道来提取动物的形状。即使用户成功设计了图像处理管道,视频帧中的意外噪声也可能会显著降低跟踪步骤中的跟踪精度。为了解决这些问题,我们提出了 UMATracker(通用多动物跟踪器),它通过可视化编程、多种跟踪算法和手动跟踪误差校正系统支持灵活的图像预处理。UMATracker 采用可视化编程用户界面,用户可以直观地设计图像处理管道。此外,该软件还使用户能够可视化图像处理的效果。我们实现了四种不同的跟踪算法,以便用户可以选择最合适的算法。此外,UMATracker 提供了手动校正工具,用于识别和校正跟踪错误。