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Dexing Cai

dblp:438/5194 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0005-8658-9964ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Virtual and augmented reality · 44% Geometric modeling and processing · 44% Multimedia systems and quality of experience · 13%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › 3d reconstruction
volumetric reconstruction
1.012026
PortaCap: Portable Volumetric Video Capturing System for Metaverse Interaction · IEEE Trans. Mob. Comput. 2026

Methods — techniques the papers use, named apart from their topics

geometric priors · 1.0data fusion · 1.0camera calibration · 1.0
YearPublicationVenuePosition
2026 PortaCap: Portable Volumetric Video Capturing System for Metaverse Interaction
abstract
Portable volumetric video capturing systems present a compelling alternative to traditional, bulky prototype systems used for streaming and interacting with volumetric content. Their key advantages, particularly flexibility and ease of deployment, make them suitable for a wide range of applications. However, despite their potential, there has been limited exploration into the design of such portable systems. This paper addresses this gap by conducting an in-depth analysis of portability and proposing an optimized camera array configuration tailored for high-quality volumetric content generation. Our approach begins with a novel, flexible camera calibration method that leverages geometric priors, enabling accurate alignment of multiple cameras without requiring specialized expertise. Building on this, we introduce a meticulous fusion technique that integrates captured and inferred data to reconstruct complete volumetric representations. This method achieves a fusion latency of less than 100 ms, ensuring real-time performance. We integrate these innovations into a portable capturing system, named PortaCap, which incorporates a carefully designed camera deployment strategy. Through both quantitative and qualitative evaluations, PortaCap demonstrates significant improvements in volumetric content quality, achieving enhancements ranging from 13% to 33.8%. These results underscore the system's potential to advance the state-of-the-art in portable volumetric video capture.
Chongli Zhang, Yakun Huang, Yuanwei Zhu, Dexing Cai, Shibo Fang, Chunsheng Wang, Xiuquan Qiao
IEEE Trans. Mob. Comput.5