Juyoung Lee

Juyoung Lee
Korea Advanced Institute of Science and Technology | KAIST · Culture Technology Research Institute

MS

About

20
Publications
5,083
Reads
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199
Citations
Citations since 2016
20 Research Items
202 Citations
2016201720182019202020212022010203040
2016201720182019202020212022010203040
2016201720182019202020212022010203040
2016201720182019202020212022010203040
Additional affiliations
September 2017 - December 2018
Korea Advanced Institute of Science and Technology
Position
  • Researcher
September 2014 - August 2018
Korea Advanced Institute of Science and Technology
Position
  • Master's Student

Publications

Publications (20)
Article
Full-text available
We present NapWell, a Sleep Assistant using virtual reality (VR) to decrease sleep onset latency by providing a realistic imagery distraction prior to sleep onset. Our proposed prototype was built using commercial hardware and with relatively low cost, making it replicable for future works as well as paving the way for more low cost EOG-VR devices...
Article
Full-text available
We present a sensor-fusion method that exploits a depth camera and a gyroscope to track the articulation of a hand in the presence of excessive motion blur. In case of slow and smooth hand motions, the existing methods estimate the hand pose fairly accurately and robustly, despite challenges due to the high dimensionality of the problem, self-occlu...
Conference Paper
Full-text available
We introduce a vision-based technique to recognize static hand poses and dynamic finger tapping gestures. Our approach employs a camera on the wrist, with a view of the opisthenar (back of the hand) area. We envisage such cameras being included in a wrist-worn device such as a smartwatch, fitness tracker or wristband. Indeed, selected off-the-shelf...
Conference Paper
To better explore the incorporation of pointing and gesturing into ubiquitous computing, we introduce WRIST, an interaction and sensing technique that leverages the dexterity of human wrist motion. WRIST employs a sensor fusion approach which combines inertial measurement unit (IMU) data from a smartwatch and a smart ring. The relative orientation...
Conference Paper
SelfSync enables rapid, robust initiation of a gesture interface using synchronized movement of different body parts. SelfSync is the gestural equivalent of a hotword such as OK-Google in a speech interface and is enabled by the increasing trend where a user wears two or more wearables, such as a smartwatch, wireless earbuds, or a smartphone. In a...
Conference Paper
In this demonstration, we will show a prototype system with sensor fusion approach to robustly track 6 degrees of freedom of hand movement and support intuitive hand gesture interaction and 3D object manipulation for Mixed Reality head-mounted displays. Robust tracking of hand and finger with egocentric camera remains a challenging problem, especia...
Conference Paper
In "Itchy Nose" we proposed a sensing technique for detecting finger movements on the nose for supporting subtle and discreet interaction. It uses the electrooculography sensors embedded in the frame of a pair of eyeglasses for data gathering and uses machine-learning technique to classify different gestures. Here we further propose an automated tr...
Conference Paper
Full-text available
We propose a sensing technique for detecting finger movements on the nose, using EOG sensors embedded in the frame of a pair of eyeglasses. Eyeglasses wearers can use their fingers to exert different types of movement on the nose, such as flicking, pushing or rubbing. These subtle gestures can be used to control a wearable computer without calling...
Conference Paper
Full-text available
SpeCam is a lightweight surface color and material sensing approach for mobile devices which only uses the front-facing camera and the display as a multi-spectral light source. We leverage the natural use of mobile devices (placing it face-down) to detect the material underneath and therefore infer the location or placement of the device. SpeCam ca...
Conference Paper
Full-text available
Orbits combines a visual display and an eye motion sensor to allow a user to select between options by tracking a cursor with the eyes as the cursor travels in a circular path around each option. Using an off-the-shelf Jins MEME pair of eyeglasses, we present a pilot study that suggests that the eye movement required for Orbits can be sensed using...
Conference Paper
Full-text available
We present a technique for detecting gestures on the edge of an unmodified smartwatch. We demonstrate two exemplary gestures, i) Sidetap -- tapping on any side and ii) Slingshot -- pressing on the edge and then releasing quickly. Our technique is lightweight, as it relies on measuring the data from the internal Inertial measurement unit (IMU) only....
Conference Paper
Solar System implements smooth pursuit eye movement interactions on commercial smart glasses using electrooculography. The system requires no calibration and little to no training. We present a prototype implementation, describe initial user tests and show several application scenarios for hands-free eye gaze interactions.
Conference Paper
Full-text available
The screen size of a smartwatch provides limited space to enable expressive multi-touch input, resulting in a markedly difficult and limited experience. We present WatchMI: Watch Movement Input that enhances touch interaction on a smartwatch to support continuous pressure touch, twist, pan gestures and their combinations. Our novel approach relies...
Conference Paper
Full-text available
In this demo, we show that it is possible to enhance touch interaction on unmodified smartwatch to support continuous pressure touch, twist and pan gestures, by only analyzing the real-time data of Inertial Measurement Unit (IMU). Our evaluation results show that the three proposed input interfaces are accurate, noise-resistant, easy to use and can...

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