Special Issue "Visual Object Tracking: Challenges and Applications"
Deadline for manuscript submissions: 30 June 2021.
Interests: computer vision; computer graphics; virtual reality; HCI
Interests: computer vision; image processing; machine learning; deep learning research problems
Visual tracking is an important and essential component of perception that has been an active research topic in the computer vision community for decades. Visual tracking algorithms have developed rapidly thanks to the massive amount of video data that in turn creates high demand for the speed and accuracy of tracking algorithms. Researchers are motivated to design faster and better methods in spite of the challenges that exist in visual tracking, especially robustness to heavy occlusions, drastic scale change, accurate localization, multi-object tracking, and recovery from failure. Despite the success in addressing numerous challenges under a wide range of circumstances, the core problems remain complex and challenging.
This main aim of this Special Issue will be to focus on the most recent advancements and trends in VOT. The methods such as those reported in the formulation of correlation filters and Siamese networks for VOT can further be explored to improve VOT performance. We invite original research work involving novel techniques, innovative methods, and useful applications that lead to significant advances in VOT. We also welcome reviews and surveys on state-of-the-art methods.
Our Special Issue will include following topics of interest but is not limited to them:
- Detection, identification, recognition, and tracking of objects using various sensors;
- Multiple camera networks or associations for very wide-range surveillance;
- Development of non-visual sensors, such as time-of-flight sensor, RGB-D camera, IR sensor, RADAR, LIDAR, motion sensor, and acoustic wave sensor, and their applications to video analysis and tracking;
- Image and video enhancement algorithms to improve the quality of visual sensors for video tracking;
- Computational photography and imaging for advanced object detection and tracking;
- Depth estimation and three-dimensional reconstruction for augmented reality (AR) and/or advanced driver assistance systems (ADAS);
- Learning data representation from video based on supervised/unsupervised/semi-supervised learning;
- Dataset and performance evaluation;
- Person re-identification, vehicle re-identification;
- Human behavior detection, human pose estimation, and tracking.
Prof. Dr. Soon Ki Jung
Dr. Sajid Javed
Manuscript Submission Information
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