Open AccessUMATracker: an intuitive image-based tracking platform
Author(s) -
Osamu Yamanaka,
Rito Takeuchi
Publication year - 2018
Publication title -
journal of experimental biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.367
H-Index - 185
eISSN - 1477-9145
pISSN - 0022-0949
DOI - 10.1242/jeb.182469
Subject(s) - computer science , preprocessor , pipeline (software) , computer vision , artificial intelligence , software , image processing , tracking (education) , frame (networking) , image (mathematics) , eye tracking , noise (video) , tracking system , digital image processing , filter (signal processing) , psychology , telecommunications , pedagogy , programming language
Image-based tracking software are regarded as valuable tools in collective animal behaviour studies. For such operations, image-pre-processing is a pre-requisite, 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, 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 also provides a manual correction tool for identifying and correcting tracking errors.