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Haojun Ni

dblp:371/3817 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0000-2036-9823ORCID · reported

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

Graphics, computer vision, multimedia, augmented reality and games · 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
Haptics and multimodal interaction · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Haptics and multimodal interaction › wearable haptic device
fingertip haptic device
0.912025
Design and Evaluation of a 6-DoF Wearable Fingertip Device for Haptic Shape Rendering · IEEE Trans. Vis. Comput. Graph. 2025
Haptics and multimodal interaction
haptic rendering
0.912025
Design and Evaluation of a 6-DoF Wearable Fingertip Device for Haptic Shape Rendering · IEEE Trans. Vis. Comput. Graph. 2025
Haptics and multimodal interaction
wearable haptic device
0.912025
Design and Evaluation of a 6-DoF Wearable Fingertip Device for Haptic Shape Rendering · IEEE Trans. Vis. Comput. Graph. 2025

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

stewart parallel mechanism · 0.9kinematic modeling · 0.9
YearPublicationVenuePosition
2025 Design and Evaluation of a 6-DoF Wearable Fingertip Device for Haptic Shape Rendering
abstract
As virtual objects contain increasingly rich attribute information, small wearable fingertip devices need to have higher degrees of freedom (DoFs) to convey the haptic sensation of virtual objects. In order to effectively display the shape features of virtual objects to users through curvature, we designed a 6-DoF wearable fingertip device (WFD). This WFD combines a 6-DoF Stewart parallel mechanism, consisting of a static platform and a mobile platform connected by six revolute-spherical-spherical kinematic chains. The translation and rotation of the mobile platform are driven by six miniature servo motors, which can simulate haptic sensations such as making and breaking contact, sliding, and skin stretch when the fingertip interacts with a virtual surface. The WFD is fixed at the user's dominant index finger using hook-and-loop fasteners, with a size of 68 × 59 × 56 mm$^{3}$3 and a mass of 45.5 g. We analyzed and validated the kinematic model of the WFD and tested its force output capability. Finally, we invited 15 adults to conduct three subjective perception experiments to evaluate the performance of the WFD in curvature perception and shape display. The experimental results show that: (1) The just noticeable difference (JND) for curvature identification using the WFD is 3.02$\pm$±0.23 m$^{-1}$-1; (2) The 6-DoF haptic feedback provided by the WFD improves the accuracy of curved surface recognition from 53.4$\pm$±7.1% in 3-DoF to 72.0$\pm$±5.9%; (3) Even without visual feedback, the shape recognition accuracy of the WFD when combined with the Touch device reaches 82.3$\pm$±8.2% . Experimental results show that the WFD has good performance and potential in curvature perception and shape display.
Dapeng Chen, Haojun Ni, Lifeng Zhu, Hong Zeng 0001, Jia Liu 0034, Aiguo Song
IEEE Trans. Vis. Comput. Graph.4