A unified toolkit for visual object tracking and segmentation evaluationČehovin Zajc, Luka (Avtor) trackingvideo segmentationperformance evaluationPythonWe present a toolkit for evaluating and analyzing visual object tracking and segmentation methods. In contrast to most existing tools, the proposed toolkit introduces a unified representation of these tasks, enabling tracking of one or more objects with different object descriptions, from points to segmentation masks. Moreover, it is organized in a modular manner, supporting multiple integration types, various experiment types, and comprehensive reporting. The toolkit’s purpose aligns with the goals of the tracking community by supporting evaluation for all VOT and VOTS challenges, as well as for several other video-tracking or segmentation datasets. It is also extensible in almost every direction (data, methods, experiment design). This paper illustrates the toolkit’s architecture and usage patterns, and discusses its role in supporting the community’s transition towards unified video understanding.20272026-10-23 12:16:08Članek v reviji190183sl