Advances in Object Tracking and Computer Vision
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 April 2026 | Viewed by 85
Special Issue Editors
Interests: computer vision; generative model; image restoration; large language model
Special Issue Information
Dear Colleagues,
Object tracking is a fundamental component of many computer vision applications, such as video surveillance, autonomous driving, human–computer interaction, and augmented reality. Its core objective is to locate and follow objects of interest across frames in a video sequence, which requires understanding object motion dynamics and adapting to various visual transformations. Over the past few decades, a wide range of tracking algorithms have been developed, from classical methods such as Kalman filters and optical flow to modern, deep learning-based techniques that leverage convolutional neural networks (CNNs), recurrent networks, transformers, and even large language models. As new challenges emerge and computational capabilities evolve, object tracking continues to be a vibrant and critical area of research.
This Special Issue aims to showcase cutting-edge research on both traditional and emerging methods in object tracking. We welcome original research articles and reviews that explore theoretical advancements, methodological innovations, and practical applications.
Topics of interests include, but are not limited to:
- Robust object tracking in complex environments;
- Multi-object tracking;
- Object tracking with image/video enhancement;
- Tracking with non-rigid and deformable objects;
- Long-term object tracking;
- Cross-modality tracking (e.g., combining RGB images, depth sensors, lidar, or thermal images);
- Tracking for autonomous systems and robotics;
- Applications in healthcare and medical imaging;
- Performance optimization for real-time tracking;
- Benchmarking and evaluation of tracking algorithms;
- Tracking for augmented and virtual reality (AR/VRvr).
Dr. Jiezhang Cao
Dr. Xia Li
Guest Editors
Manuscript Submission Information
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Keywords
- computer vision
- object tracking
- multi-object tracking
- long-term object tracking
- image segmentation
- image/video enhancement
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