CAFI-AR

Author:

Tang Xiao1ORCID,Li Ruihui2ORCID,Fu Chi-Wing3ORCID

Affiliation:

1. The Chinese University of Hong Kong, Hong Kong, China

2. Hunan University, Hunan, China

3. The Chinese University of Hong Kong, Hong Kong, China and Institute of Medical Intelligence and XR, The Chinese University of Hong Kong, Hong Kong, China

Abstract

Freehand interaction enhances user experience, allowing one to use bare hands to manipulate virtual objects in AR. Yet, it remains challenging to accurately and efficiently detect contacts between real hand and virtual object, due to the imprecise captured/estimated hand geometry. This paper presents CAFI-AR, a new approach for Contact-Aware Freehand Interaction with virtual AR objects, enabling us to automatically detect hand-object contacts in real-time with low latency. Specifically, we formulate a compact deep architecture to efficiently learn to predict hand action and contact moment from sequences of captured RGB images relative to the 3D virtual object. To train the architecture for detecting contacts on AR objects, we build a new dataset with 4,008 frame sequences, each with annotated hand-object interaction information. Further, we integrate CAFI-AR into our prototyping AR system and develop various interactive scenarios, demonstrating fine-grained contact-aware interactions on a rich variety of virtual AR objects, which cannot be achieved by existing AR interaction approaches. Lastly, we also evaluate CAFI-AR, quantitatively and qualitatively, through two user studies to demonstrate its effectiveness in terms of accurately detecting the hand-object contacts and promoting fluid freehand interactions

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MRehab: A Mixed Reality Rehabilitation System Supporting Integrated Speech and Hand Training;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2024-08-22

2. Deep Learning in Distance Awareness Using Deep Learning Method;Lecture Notes in Networks and Systems;2024

3. SA-Fusion: Multimodal Fusion Approach for Web-based Human-Computer Interaction in the Wild;Proceedings of the ACM Web Conference 2023;2023-04-30

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