Recent Developments in Object Tracking and Computer Vision
A special issue of Electronics (ISSN 2079-9292).
Deadline for manuscript submissions: 15 May 2026 | Viewed by 23
Special Issue Editors
Interests: computer vision; scene understanding; multimodal learning; segmentation; medical image analysis
Interests: computer vision; brain-inspired computing; digital humans; medical data analysis
Interests: video object tracking; sign language recognition and translation; event-based deblurring
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Object tracking and computer vision technologies have become key enablers in a wide range of applications across industries, from autonomous driving, robotics, and intelligent surveillance to healthcare, smart manufacturing, and augmented reality. With the rapid progress in deep learning, edge computing, and multimodal data fusion, the field has achieved remarkable advances in accuracy, robustness, and real-time performance.
This Special Issue aims to collect cutting-edge research and innovative solutions addressing a broad spectrum of tasks in object tracking, segmentation, and computer vision. We welcome contributions not only in traditional visual tracking but also in related domains such as human pose estimation and tracking, cell tracking in biomedical imaging, and segmentation tasks in complex industrial and medical applications. Our focus is on novel algorithms, system designs, benchmark datasets, and application-driven research that advance the state of the art in both theory and practice.
Topics of interest include, but are not limited to, the following:
- Object detection, segmentation, and tracking in static and dynamic scenes;
- Multi-object, long-term, and large-scale tracking methods;
- Human pose estimation and tracking across modalities;
- Cell and particle tracking in biomedical and microscopy data;
- Industrial visual inspection and medical image segmentation;
- Robust tracking and segmentation under occlusion, illumination change, and complex motion;
- Multimodal and cross-domain approaches (e.g., depth, thermal, LiDAR);
- Real-time vision systems and edge computing solutions;
- Benchmark datasets, evaluation protocols, and performance analysis.
We warmly invite submissions of original research papers, innovative methodologies, and comprehensive review articles that contribute to the advancement of object tracking, segmentation, and broader computer vision tasks.
Dr. Wei Ji
Dr. Shihao Zou
Dr. Pengyu Zhang
Guest Editors
Manuscript Submission Information
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Keywords
- object tracking
- object detection
- image segmentation
- multimodal fusion
- computer vision
- deep learning
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