EDBT 2026 Demo / reviewers in the wild / expert
Ping-Jung Duh
dblp:295/4636
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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.
| Artificial intelligence
1 paper |
Robot navigation and mapping · 77% Segmentation and scene understanding · 23% | |
| Human-computer interaction and pervasive computing
1 paper |
Accessibility and assistive technology · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping › localization
global localization |
0.5 | 1 | 2021 | V-Eye: A Vision-Based Navigation System for the Visually Impaired · IEEE Trans. Multim. 2021 |
Accessibility and assistive technology › assistive navigation
navigation assistance for visually impaired |
0.5 | 1 | 2021 | V-Eye: A Vision-Based Navigation System for the Visually Impaired · IEEE Trans. Multim. 2021 |
Computer vision › Segmentation and scene understanding
image segmentation |
0.1 | 1 | 2021 | V-Eye: A Vision-Based Navigation System for the Visually Impaired · IEEE Trans. Multim. 2021 |
Methods — techniques the papers use, named apart from their topics
image segmentation · 1.0VB-GPS · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | V-Eye: A Vision-Based Navigation System for the Visually ImpairedabstractNumerous systems for helping visually impaired people navigate in unfamiliar places have been proposed. However, few can detect and warn about moving obstacles, provide correct orientation in real time, or support navigation between indoor and outdoor spaces. Accordingly, this paper proposes V-Eye, which fulfills these needs by utilizing a novel global localization method (VB-GPS) and image-segmentation techniques to achieve better scene understanding with a single camera. Our experiments establish that the proposed system can reliably provide precise locations and orientation information (with a median error of approximately 0.27 m and 0.95°); detect unpredictable obstacles; and support navigating both within and between indoor and outdoor environments. The results of a user-experience study of V-eye further indicate that it helped the participants not only with navigation, but also improved their awareness of obstacles, enhanced their spatial awareness more generally, and led them to feel more secure and independent while walking. Ping-Jung Duh, Yu-Cheng Sung, Liang-Yu Fan Chiang, Yung-Ju Chang, Kuan-Wen Chen |
IEEE Trans. Multim. | 1 |