Demo Data from EDBT 2026 / reviewers in the wild / expert
Weizhi Nai
dblp:194/9593
· DBLP profile ↗
4ranked-venue papers
1as first author
2since 2021 · last 2024
0000-0002-2447-1814ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 since 2021Artificial intelligence and machine learning · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 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.
| Human-computer interaction and pervasive computing
1 paper |
Interaction techniques and input · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interaction techniques and input › spatial interaction › 3d interaction
3d selection |
0.8 | 1 | 2024 | Accurate Raycasting Selection With Rotation Gesture Using a 6-DOF Tracking Device · IEEE Trans. Vis. Comput. Graph. 2024 |
Interaction techniques and input › input device › 3d input device
6-DOF input device |
0.8 | 1 | 2024 | Accurate Raycasting Selection With Rotation Gesture Using a 6-DOF Tracking Device · IEEE Trans. Vis. Comput. Graph. 2024 |
Interaction techniques and input › spatial interaction › 3d interaction
raycasting |
0.8 | 1 | 2024 | Accurate Raycasting Selection With Rotation Gesture Using a 6-DOF Tracking Device · IEEE Trans. Vis. Comput. Graph. 2024 |
Methods — techniques the papers use, named apart from their topics
rotation gesture detection · 0.8control-display gain · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Accurate Wide-Range Scaling Manipulation of the Model with a 6-DOF Tracking DeviceabstractIn virtual reality applications, translation, orientation, and scaling are the three basic properties of 3D model manipulation. The 6-DOF tracking device can be used to directly manipulate the former two properties. However, the scaling property cannot be directly mapped with a hand-held tracking device because it is physically impossible. In this study, we first compare various schemes for mapping the translation and orientation of a handheld tracking device to the 3D model’s scaling property. Next, we propose a scaling manipulation framework that combines the advantages of different schemes. This enables accurate and natural wide-range scaling with the orthogonal combination design of the translation and orientation data of the tracking device. The efficiency and accuracy of the proposed framework were examined in a user study, which verified that it improved the scaling error of wide-range scaling by over 55% without a significant decrease in time performance. Finally, two scaling scenarios for the application of this framework were presented. Weizhi Nai, Xiaoying Sun |
Int. J. Hum. Comput. Interact. | 2 |
| 2024 | Accurate Raycasting Selection With Rotation Gesture Using a 6-DOF Tracking DeviceabstractA six degrees of freedom (6-DOF) controller is a commonly used input device in three-dimensional user interface (3DUI) applications. However, for the fundamental task of target selection in 3D space, the selection accuracy decreases owing to the Heisenberg effect during the manipulation of the 6-DOF controller. Based on the pointing action of a 6-DOF device, we establish the mathematical model for raycasting and analyze the possibility of using a rotation gesture to select a target. This study proposes a target selection method using the axial rotation of the user's wrist, which reduces the negative impact of a discrete input for triggering the selection on accuracy. The detection model can identify the start time of the user's rotation action. The custom designed control display gain (CD gain) function can maintain the ray's stability during the rotation gesture. This method was verified using a 6-DOF pen and Vive controller in three experiments. The results show that the accuracy of the proposed rotation gesture-based raycasting target selection method is superior to that of the traditional button-pressing method, and it can be integrated into existing tracking systems for further application. Weizhi Nai, Xiaoying Sun |
IEEE Trans. Vis. Comput. Graph. | 2 |
| 2019 | Tactile sensitivity in ultrasonic haptics: Do different parts of hand and different rendering methods have an impact on perceptual threshold?abstractBackground Ultrasonic tactile representation utilizes focused ultrasound to create tactile sensations on the bare skin of a user’s hand that is not in contact with a device. This study is a preliminary investigation on whether different ultrasonic haptic rendering methods have an impact on the perceptual threshold. Methods This study conducted experiments with the adaptive step method to obtain participants’ perceptual thresholds. We examine (1) whether different parts on the palm of the hand have different perceptual thresholds; (2) whether the perceptual threshold is different when the ultrasonic focus point is stationary and when it moves in different trajectories; (3) whether different moving speeds of the ultrasonic focus point have an influence on the perceptual threshold; and (4) whether the addition of a DC offset to the modulating wave has an impact on the perceptual threshold. Results The results show that the center of the palm is more sensitive to ultrasonic haptics than the fingertip; compared with a fast-moving focus point, the palm is more sensitive to a stationary and slow-moving focus point. When the modulating wave has a DC offset, the palm is sensitive to a much smaller modulation amplitude . Conclusion For the future ultrasonic tactile representation systems, dynamic adjustment of intensity is required to compensate the difference in perceptual thresholds under different rendering methods to achieve more realistic ultrasonic haptics. Chongyang Sun, Weizhi Nai, Xiaoying Sun |
Virtual Real. Intell. Hardw. | 2 |
| 2017 | Fast hand posture classification using depth features extracted from random line segments
Weizhi Nai, Yue Liu 0005, David Rempel, Yongtian Wang |
Pattern Recognit. | 1 |