Interpretable Control of Track Initiation with Predefined Intervention Bounds in Unmanned Aerial Vehicle Perception Systems

In aerial monitoring systems, a single detection error may develop into a persistent false track and affect data passed to downstream components. The study aims to reduce such errors while bounding the scale of intervention in advance and retaining a traceable account of each decision. An external method is proposed that briefly delays low-support track-initiation episodes. The number of delays is controlled by an accumulated budget, while the support estimate, current budget balance, reason for intervention, and final status are recorded for each episode. The method was evaluated on seven video sequences from a publicly available aerial-imagery dataset containing small objects, partial occlusions, and substantial scale changes. Three tracking algorithms and a supervised ensemble of decision trees were compared. For ByteTrack, the delay was applied to 2.62 percent of track-initiation episodes, removing 425 false observations and 176 false initiations from the operational output, while the change in the combined precision-recall measure remained within the predefined tolerance. For OC-SORT and SORT, the reduction in false observations was not confirmed under the adopted statistical criterion. An examination of 29,385 initial video fragments found no violations of the predefined limits. The additional processing time averaged 0.901 milliseconds per frame. The results show that a short delay can reduce the number of false observations while keeping the scale of intervention under control.

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