Computer Vision for Scene Understanding in Immersive Environments
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".
Deadline for manuscript submissions: 31 July 2026
Special Issue Editors
Interests: augmented reality; virtual reality; metaverse; digital twin; spatial information; GIS; computer vision
Special Issue Information
Dear Colleagues,
Immersive Environments—encompassing Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR)—are fundamentally changing human interaction with digital and physical spaces. Central to crafting engaging immersive experiences is computer vision, empowering machines to perceive, interpret, and interact with complex 3D scenes. Developing computer vision for these systems is multidisciplinary, drawing from artificial intelligence, sensor technology, 3D geometry, computer graphics, and human perception.
Recent breakthroughs in deep learning, sensor fusion (especially with camera sensors), and real-time processing are accelerating immersive system capabilities. Concurrently, these advancements introduce pressing scene understanding challenges: the robust real-time understanding of dynamic scenes via visual data; interpreting human presence and actions captured by cameras; seamlessly blending virtual and real elements with precise visual registration; and ensuring systems understand user movement and environmental changes via cameras for safety and contextual awareness. These demand innovations in visual perception.
This Special Issue, “Computer Vision for Scene Understanding in Immersive Environments”, invites high-quality original research and insightful survey papers from academics and industry experts. We are particularly interested in contributions exploring novel methods and applications in areas including, but not limited to, the following:
- Camera-based real-time 3D reconstruction, semantic mapping, and SLAM adaptable to environmental changes and user movement.
- Object detection, tracking, and pose estimation in dynamic scenes for AR/VR/MR interaction.
- Camera-based human pose estimation, activity/gaze analysis, and interaction modeling.
- Generative models for visual-guided scene creation, augmentation, and virtual–real interactions.
- New datasets, benchmarks, and evaluation methods for camera-driven immersive scene understanding.
- Applications of scene understanding in AR, VR, and MR (including spatial computing) across robotics, healthcare, education, entertainment, and autonomous systems, focusing on camera-based environmental perception and user interactions.
We encourage submissions presenting significant theoretical advancements, innovative algorithms, and compelling practical applications, fostering dialogue on evolving intelligent immersive technologies.
Dr. Ahyun Lee
Dr. Sunglok Choi
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- computer vision
- machine learning
- augmented reality
- virtual reality
- mixed reality
- simultaneous localization and mapping
- scene understanding
- human–computer interactions
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