Reproducible Evaluation of Pan-Tilt-Zoom Tracking
Gengjie Chen, Pierre-Luc St-Charles, Wassim Bouachir, Thomas, Joeisseint, Guillaume-Alexandre Bilodeau, Robert Bergevin

TL;DR
This paper introduces a standardized evaluation framework for PTZ tracking algorithms using a virtual camera, enabling consistent and reproducible assessment of tracking performance under realistic conditions.
Contribution
The paper presents a novel evaluation framework for PTZ tracking that simulates real camera behavior, addressing the lack of standardization in the field.
Findings
Framework effectively replicates real PTZ camera behavior
Baseline results established with Camshift tracker
Enables reproducible and consistent evaluation scenarios
Abstract
Tracking with a Pan-Tilt-Zoom (PTZ) camera has been a research topic in computer vision for many years. However, it is very difficult to assess the progress that has been made on this topic because there is no standard evaluation methodology. The difficulty in evaluating PTZ tracking algorithms arises from their dynamic nature. In contrast to other forms of tracking, PTZ tracking involves both locating the target in the image and controlling the motors of the camera to aim it so that the target stays in its field of view. This type of tracking can only be performed online. In this paper, we propose a new evaluation framework based on a virtual PTZ camera. With this framework, tracking scenarios do not change for each experiment and we are able to replicate online PTZ camera control and behavior including camera positioning delays, tracker processing delays, and numerical zoom. We tested…
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Taxonomy
TopicsVideo Surveillance and Tracking Methods · Advanced Vision and Imaging · Visual Attention and Saliency Detection
