2. Next Gen Input

会議の名前
UIST 2024
PointerVol: A Laser Pointer for Swept Volumetric Displays
要旨

A laser pointer is a commonly used device that does not require communication with the display system or modifications on the applications, the presenter can just take a pointer and start using it. When a laser pointer is used on a volumetric display, a line rather than a point appears, making it not suitable for pointing at 3D locations. PointerVol is a modified laser pointer that allows users to point to 3D positions inside a swept volumetric display. We propose two PointerVol implementations based on timing and distance measurements, we evaluate the pointing performance using them. Finally, we present other features such as multi-user pointing, line patterns and a multi-finger wearable. PointerVol is a simple device that can help to popularize volumetric displays, or at least to make them more usable for presentations with true-3D content.

著者
Unai Javier Fernández
Universidad Pública de Navarra, Pamplona, Spain
Iosune Sarasate Azcona
Universidad Pública de Navarra, Pamplona, Spain
Iñigo Ezcurdia
Public University of Navarra, Pamplona, Spain
Manuel Lopez-Amo
Universidad Pública de Navarra, Pamplona, Spain
Ivan Fernández
Universidad Pública de Navarra, Pamplona, Spain
Asier Marzo
Universidad Publica de Navarra, Pamplona, Navarre, Spain
論文URL

https://doi.org/10.1145/3654777.3676432

動画
RFTIRTouch: Touch Sensing Device for Dual-sided Transparent Plane Based on Repropagated Frustrated Total Internal Reflection
要旨

Frustrated total internal reflection (FTIR) imaging is widely applied in various touch-sensing systems. However, vision-based touch sensing has structural constraints, and the system size tends to increase. Although a sensing system with reduced thickness has been developed recently using repropagated FTIR (RFTIR), it lacks the property of instant installation anywhere because observation from the side of a transparent medium is required. Therefore, this study proposes an "RFTIRTouch" sensing device to capture RFTIR images from the contact surface. RFTIRTouch detects the touch position on a dual-sided plane using a physics-based estimation and can be retrofitted to existing transparent media with simple calibration. Our evaluation experiments confirm that the touch position can be estimated within an error of approximately 2.1 mm under optimal conditions. Furthermore, several application examples are implemented to demonstrate the advantages of RFTIRTouch, such as its ability to measure dual sides with a single sensor and waterproof the contact surface.

著者
Ratchanon Wattanaparinton
Tokai University, Hiratsuka, Japan
Kotaro Kitada
Tokai University, Hiratsuka, Japan
Kentaro Takemura
Tokai University, Hiratsuka, Japan
論文URL

https://doi.org/10.1145/3654777.3676428

動画
IRIS: Wireless Ring for Vision-based Smart Home Interaction
要旨

Integrating cameras into wireless smart rings has been challenging due to size and power constraints. We introduce IRIS, the first wireless vision-enabled smart ring system for smart home interactions. Equipped with a camera, Bluetooth radio, inertial measurement unit (IMU), and an onboard battery, IRIS meets the small size, weight, and power (SWaP) requirements for ring devices. IRIS is context-aware, adapting its gesture set to the detected device, and can last for 16-24 hours on a single charge. IRIS leverages the scene semantics to achieve instance-level device recognition. In a study involving 23 participants, IRIS consistently outpaced voice commands, with a higher proportion of participants expressing a preference for IRIS over voice commands regarding toggling a device's state, granular control, and social acceptability. Our work pushes the boundary of what is possible with ring form-factor devices, addressing system challenges and opening up novel interaction capabilities.

著者
Maruchi Kim
University of Washington, Seattle, Washington, United States
Antonio Glenn
University of Washington, Seattle, Washington, United States
Bandhav Veluri
University of Washington, Seattle, Washington, United States
Yunseo Lee
University of Washington, Seattle, Washington, United States
Eyoel Gebre
University of Washington, Seattle, Washington, United States
Aditya Bagaria
University of Washington, Seattle, Washington, United States
Shwetak Patel
University of Washington, Seattle, Washington, United States
Shyamnath Gollakota
University of Washington, Seattle, Washington, United States
論文URL

https://doi.org/10.1145/3654777.3676327

動画
Silent Impact: Tracking Tennis Shots from the Passive Arm
要旨

Wearable technology has transformed sports analytics, offering new dimensions in enhancing player experience. Yet, many solutions involve cumbersome setups that inhibit natural motion. In tennis, existing products require sensors on the racket or dominant arm, causing distractions and discomfort. We propose Silent Impact, a novel and user-friendly system that analyzes tennis shots using a sensor placed on the passive arm. Collecting Inertial Measurement Unit sensor data from 20 recreational tennis players, we developed neural networks that exclusively utilize passive arm data to detect and classify six shots, achieving a classification accuracy of 88.2% and a detection F1 score of 86.0%, comparable to the dominant arm. These models were then incorporated into an end-to-end prototype, which records passive arm motion through a smartwatch and displays a summary of shots on a mobile app. User study (N=10) showed that participants felt less burdened physically and mentally using Silent Impact on the passive arm. Overall, our research establishes the passive arm as an effective, comfortable alternative for tennis shot analysis, advancing user-friendly sports analytics.

著者
Junyong Park
KAIST, Daejeon, Korea, Republic of
Saelyne Yang
School of Computing, KAIST, Daejeon, Korea, Republic of
Sungho Jo
KAIST, Daejeon, Korea, Republic of
論文URL

https://doi.org/10.1145/3654777.3676403

動画