Computer Vision Methods for Motion Control and Analysis
A special issue of Applied Sciences (ISSN 2076-3417).
Deadline for manuscript submissions: 20 October 2025 | Viewed by 1075
Special Issue Editors
Interests: computer vision; multimodal data/signals; signal processing
Interests: real-time image and signal processing; development of intelligent systems; application of intelligent systems; beekeeping
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Computer vision, a multidisciplinary field combining computer science, artificial intelligence, and signal processing, plays a critical role in modern technological advancements. It focuses on enabling machines to interpret and understand the visual world, mimicking the capabilities of human vision. One of the applications within this domain is motion control and analysis, which involves the detection, tracking, and interpretation of movement in visual data. This rapidly evolving field combines advanced image processing techniques with machine learning algorithms to extract meaningful information from visual data, enabling precise motion tracking, interpretation, and control. This research area is fundamental to a wide array of applications, including robotics, industrial automation, autonomous vehicles, healthcare, sports analytics, and human–computer interactions.
The aim of this Special Issue is to consolidate recent advancements and novel methodologies in computer vision that enhance motion control and analysis. By bringing together contributions from leading researchers and practitioners, this issue seeks to address current challenges, propose innovative solutions, and outline future directions for research. This Special Issue covers a wide range of topics, including but not limited to the following:
- Deep learning approaches for understanding motion;
- Motion detection and tracking algorithms;
- Human motion analysis, gesture, and activity recognition;
- Real-time motion analysis;
- Vision-based control systems for robotics;
- Multimodal data fusion for motion analysis;
- Machine learning and deep learning techniques for motion interpretation;
- Applications in robotics, autonomous systems, and human–machine interfaces;
- Motion prediction and trajectory planning;
- Applications in automation, healthcare, sports, and entertainment.
This Special Issue aims to highlight the significance of integrating advanced computer vision techniques into motion control and analysis systems, ultimately contributing to the development of more intelligent and responsive technologies.
Prof. Dr. Dalius Matuzevičius
Prof. Dr. Artūras Serackis
Dr. Julius Griškevičius
Guest Editors
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Keywords
- deep learning approaches for understanding motion
- motion detection and tracking algorithms
- human motion analysis, gesture, and activity recognition
- real-time motion analysis
- vision-based control systems for robotics
- multimodal data fusion for motion analysis
- machine learning and deep learning techniques for motion interpretation
- applications in robotics, autonomous systems, and human–machine interfaces
- motion prediction and trajectory planning
- applications in automation, healthcare, sports, and entertainment
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