Guest Editors
Prof. Miguel A. Patricio
Email: mpatrici@inf.uc3m.es
Affiliation: Computer Science and Engineering Department, Universidad Carlos III de Madrid, Colmenarejo, Madrid, 28270, Spain
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Research Interests: computer vision, machine learning, multi-agent systems, deep learning, evolutionary computation, decision making
Prof. Juan P. Llerena
Email: jp.llerena@uah.es
Affiliation: Cognitive Science Research Group, Universidad de Alcalá, Alcalá de Henares, Madrid, 28805, Spain
Homepage:
Research Interests: machine learning, deep learning, information fusion, computer vision, tracking, image/video segmentation, drones systems, probabilistic planning, evolutinary computing
Summary
Video object tracking plays a pivotal role in modern computer vision systems and applications, enabling the understanding of dynamic scenes across diverse domains such as surveillance, autonomous navigation, human activity recognition, and smart cities among others. As scenes become more crowded and complex, tracking systems must robustly address challenges like occlusion, identity switching, motion prediction, and data association.
This Special Issue aims to bring together novel research contributions in video object tracking, with a focus on both methodological advancements and applied solutions. Topics of interest include single and multiple object tracking, online/offline tracking, and hybrid pipelines that combine deep learning with classical techniques such as filtering, assignment algorithms, or geometric modelling. Special attention will be given to works addressing tracking in complex scenarios—including crowded scenes, adverse visibility, and high-risk environments.
We particularly welcome submissions that present improvements in data association, long-term tracking, occlusion handling, and identity preservation, as well as system-level contributions integrating detection, tracking, and motion prediction. Studies applied to security, surveillance, and defense contexts are also strongly encouraged, especially those demonstrating robustness and adaptability in real-world conditions.
Potential topics include, but are not limited to:
· Single-Object Tracking
· Multi-Object Tracking
· Tracking-by-Detection
· Online/Offline Object Tracking
· Long-Term Tracking
· Robust Tracking
· Embedding-Based Tracking
· Object Re-identification
· Filters for Tracking
· Data Association
· Motion Estimation and Prediction
· Cross-domain and multi-modal tracking
· Tracking Evaluation Metrics
· Synthetic and Benchmark Datasets
Keywords
Computer Vision, Single-Object Tracking, Multiple-Object Tracking,Online/Offline Object Tracking, Embedding-Based Tracking, Long-Term Tracking.
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