36,236 research outputs found
Freeform User Interfaces for Graphical Computing
報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専
3DTouch: A wearable 3D input device with an optical sensor and a 9-DOF inertial measurement unit
We present 3DTouch, a novel 3D wearable input device worn on the fingertip
for 3D manipulation tasks. 3DTouch is designed to fill the missing gap of a 3D
input device that is self-contained, mobile, and universally working across
various 3D platforms. This paper presents a low-cost solution to designing and
implementing such a device. Our approach relies on relative positioning
technique using an optical laser sensor and a 9-DOF inertial measurement unit.
3DTouch is self-contained, and designed to universally work on various 3D
platforms. The device employs touch input for the benefits of passive haptic
feedback, and movement stability. On the other hand, with touch interaction,
3DTouch is conceptually less fatiguing to use over many hours than 3D spatial
input devices. We propose a set of 3D interaction techniques including
selection, translation, and rotation using 3DTouch. An evaluation also
demonstrates the device's tracking accuracy of 1.10 mm and 2.33 degrees for
subtle touch interaction in 3D space. Modular solutions like 3DTouch opens up a
whole new design space for interaction techniques to further develop on.Comment: 8 pages, 7 figure
miMic: The microphone as a pencil
miMic, a sonic analogue of paper and pencil is proposed: An augmented microphone for vocal and gestural sonic sketching. Vocalizations are classified and interpreted as instances of sound models, which the user can play with by vocal and gestural control. The physical device is based on a modified microphone, with embedded inertial sensors and buttons. Sound models can be selected by vocal imitations that are automatically classified, and each model is mapped to vocal and gestural features for real-time control. With miMic, the sound designer can explore a vast sonic space and quickly produce expressive sonic sketches, which may be turned into sound prototypes by further adjustment of model parameters
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Pictures in Your Mind: Using Interactive Gesture-Controlled Reliefs to Explore Art
Tactile reliefs offer many benefits over the more classic raised line drawings or tactile diagrams, as depth, 3D shape, and surface textures are directly perceivable. Although often created for blind and visually impaired (BVI) people, a wider range of people may benefit from such multimodal material. However, some reliefs are still difficult to understand without proper guidance or accompanying verbal descriptions, hindering autonomous exploration.
In this work, we present a gesture-controlled interactive audio guide (IAG) based on recent low-cost depth cameras that can be operated directly with the hands on relief surfaces during tactile exploration. The interactively explorable, location-dependent verbal and captioned descriptions promise rapid tactile accessibility to 2.5D spatial information in a home or education setting, to online resources, or as a kiosk installation at public places.
We present a working prototype, discuss design decisions, and present the results of two evaluation studies: the first with 13 BVI test users and the second follow-up study with 14 test users across a wide range of people with differences and difficulties associated with perception, memory, cognition, and communication. The participant-led research method of this latter study prompted new, significant and innovative developments
A fast and robust hand-driven 3D mouse
The development of new interaction paradigms requires a natural interaction. This means that people should be able to interact with technology with the same models used to interact with everyday real life, that is through gestures, expressions, voice. Following this idea, in this paper we propose a non intrusive vision based tracking system able to capture hand motion and simple hand gestures. The proposed device allows to use the hand as a "natural" 3D mouse, where the forefinger tip or the palm centre are used to identify a 3D marker and the hand gesture can be used to simulate the mouse buttons. The approach is based on a monoscopic tracking algorithm which is computationally fast and robust against noise and cluttered backgrounds. Two image streams are processed in parallel exploiting multi-core architectures, and their results are combined to obtain a constrained stereoscopic problem. The system has been implemented and thoroughly tested in an experimental environment where the 3D hand mouse has been used to interact with objects in a virtual reality application. We also provide results about the performances of the tracker, which demonstrate precision and robustness of the proposed syste
Robust 3D Action Recognition through Sampling Local Appearances and Global Distributions
3D action recognition has broad applications in human-computer interaction
and intelligent surveillance. However, recognizing similar actions remains
challenging since previous literature fails to capture motion and shape cues
effectively from noisy depth data. In this paper, we propose a novel two-layer
Bag-of-Visual-Words (BoVW) model, which suppresses the noise disturbances and
jointly encodes both motion and shape cues. First, background clutter is
removed by a background modeling method that is designed for depth data. Then,
motion and shape cues are jointly used to generate robust and distinctive
spatial-temporal interest points (STIPs): motion-based STIPs and shape-based
STIPs. In the first layer of our model, a multi-scale 3D local steering kernel
(M3DLSK) descriptor is proposed to describe local appearances of cuboids around
motion-based STIPs. In the second layer, a spatial-temporal vector (STV)
descriptor is proposed to describe the spatial-temporal distributions of
shape-based STIPs. Using the Bag-of-Visual-Words (BoVW) model, motion and shape
cues are combined to form a fused action representation. Our model performs
favorably compared with common STIP detection and description methods. Thorough
experiments verify that our model is effective in distinguishing similar
actions and robust to background clutter, partial occlusions and pepper noise
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