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Electronics
Special Issues
User-Centered Interaction Design: Latest Advances and Prospects
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User-Centered Interaction Design: Latest Advances and Prospects

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 386

Special Issue Editors

Dr. Xiaokun Wang

E-Mail Website
Guest Editor
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: graphics and virtual reality; intelligent simulation; human-computer interaction
Dr. Yalan Zhang

E-Mail Website
Guest Editor
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: intelligent modeling and simulation; 3D visualization
Dr. Jun Zhou

E-Mail Website
Guest Editor
The Department of Computer Science, Yale University, New Haven, CT 06520, USA
Interests: graphics; human-computer interaction

Special Issue Information

Dear Colleagues,

User-centered interaction design (UCID) has become a cornerstone in the evolution of human–computer interaction. As digital technologies such as artificial intelligence, virtual reality, and ubiquitous computing increasingly permeate daily life, they are reshaping how users interact with devices and services. These advanced technologies, often operating behind intuitive interfaces that employ natural human communication methods—such as voice, gestures, and emotions—make sophisticated systems more accessible and user-friendly.

This Special Issue aims to explore the latest advancements in UCID, with a focus on emerging trends and design strategies that foster adaptive, personalized, and context-aware user experiences. We are particularly interested in research that integrates these technologies into designs that prioritize inclusivity, accessibility, and user empowerment.

Looking toward the future, the rapid expansion of interconnected digital ecosystems raises critical questions around privacy, ethics, and user autonomy. As interaction systems become more deeply embedded in both personal and social spheres, it is essential to consider their broader societal impact. This Special Issue aims to gather high-quality research that addresses the opportunities, challenges, and future prospects of user-centered interaction design, laying the foundation for next-generation user experiences.

Dr. Xiaokun Wang
Dr. Yalan Zhang
Dr. Jun Zhou
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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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

  • user-centered design
  • context-aware interfaces
  • adaptive technologies
  • personalized interaction
  • wearable technologies
  • virtual/augmented/mixed reality
  • inclusive user experience
  • ethics in interaction design
  • smart systems

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Published Papers (1 paper)

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Research

15 pages, 6238 KiB  
Article
Interactive Instance Search: User-Centered Enhanced Image Retrieval with Learned Perceptual Image Patch Similarity
by Zikun Li, Shige Lu, Zhaolin Yuan, Bowen Hou and Jilong Bian
Electronics 2025, 14(9), 1766; https://doi.org/10.3390/electronics14091766 - 27 Apr 2025
Viewed by 150
Abstract
Instance searches pertain to the identification of specific objects or scenes within a dataset that correspond to a given query image. The existing research primarily concentrates on improving the accuracy of machine-recognized instances, frequently neglecting the pivotal role of human–computer interaction. As a [...] Read more.
Instance searches pertain to the identification of specific objects or scenes within a dataset that correspond to a given query image. The existing research primarily concentrates on improving the accuracy of machine-recognized instances, frequently neglecting the pivotal role of human–computer interaction. As a result, effectively searching for instances that align with user preferences continues to pose a substantial challenge. In this paper, we introduce an intuitive and efficient instance search method that incorporates human–computer interaction. Specifically, our proposed interactive instance search system includes tools that enable users to directly highlight specific instances of interest within the query image. Furthermore, we propose the use of learned perceptual image patch similarity to effectively bridge the semantic gap between low-level features and high-level semantics. Contrary to conventional metrics, such as cosine similarity, which rely on pixel-level or superficial feature comparisons, we employ deep neural networks to model perceptual differences in a hierarchical manner. The experimental results demonstrate that our approach surpasses traditional methods in terms of similarity-matching accuracy and exhibits robust performance on datasets such as Oxford5k and Paris6k. Full article
(This article belongs to the Special Issue User-Centered Interaction Design: Latest Advances and Prospects)
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