EVALUATION OF THE ROBUSTNESS OF MULTIPLE OBJECT TRACKING METHODS TO PARTIAL OCCLUSIONS IN VIDEO SEQUENCES

Abstract

The article addresses the problem of robust multiple object tracking in video sequences under partial occlusions, short-term detection loss, and object scale reduction. The relevance of the study is determined by the fact that in real video data, objects are often partially hidden by scene elements, overlaid graphical objects, or other moving objects, which may lead to track loss and identity changes. The objective of the paper is to evaluate the robustness of multiple object tracking methods to partial occlusions using ByteTrack and BoT-SORT as examples. The experimental study is based on the tracking-by-detection approach with YOLOv8 used as the object detector. Tracking quality is evaluated using detection rate, failure rate, number of unique track identifiers, main track length, average track length, and track fragmentation indicators. The obtained results show that BoT-SORT produces fewer unique tracks and a longer main track, while ByteTrack demonstrates a slightly lower number of internal track segments. It is concluded that BoT-SORT is a suitable main option for further research on object tracking under partial occlusions.