I am currently involved in GLAnceable Nuances for Contextual Events (GLANCE) project supported by EPSRC. My ambition is to understand the visual context of egocentric videos for adaptive visual guidance tailored to a user.
Human Behaviour/Affect Understanding
I was involved in SensingFeeling project supported by Innovative UK. I proposed SmileNet, which is the first smiling face detection network that does not require pre-processing such as face detection and registration in advance to generate a normalised input image.
Research interests: Deep learning, affective computing, behaviour understanding
Unified Visual Perception Model for Context-aware Augmented Reality (Multiple Object)
We propose unified visual perception model, which imitates the human visual perception process, for the stable object recognition necessarily required for augmented reality (AR) in the field. The proposed model is designed based on the theoretical bases in the field of cognitive informatics, brain research and psychological science.
- ISMAR 2013: DC program (officially, poster), Adelaide, S.A, Australia, Oct. 1-4, 2013.
Local Feature Descriptors for 3D Object Recognition
This paper represents 3D object recognition, which is an extension of the common feature point-based object recognition, based on novel descriptors utilizing local angles (for shape), gradient orientations (for texture of corners), and color information.
Semi-automatic ROI Detection for In-Situ Painting Recognition
In the case of illumination and view direction changes, the ability to accurately detect the Regions of Interest (ROI) is important for robust recognition. In this paper, we propose a stroke-based semi-automatic ROI detection algorithm using adaptive thresholding and a Hough-transform method for in-situ painting recognition.
This paper presents an adaptive lip feature point detection algorithm for the proposed real-time smile training system using visual instructions. The proposed algorithm can detect a lip feature point irrespective of lip color with minimal user participation, such as drawing a line on a lip on the screen. Therefore, the proposed algorithm supports adaptive feature detection by real-time analysis for a color histogram. Moreover, we develop a supportive guide model as visual instructions for the target expression. By using the guide model, users can train their smile expression intuitively because they can easily identify the differences between their smile and target expression.
- The 4th International Conference on E-Learning and Games (Edutainment 2009): PDF, VIDEO
Finger Vein Recognition
With increases in recent security requirements, biometric images such as fingerprints, faces and irises have been widely used in many recognition applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins to identify individuals at a high level of accuracy. This paper proposes new devices and algorithms for touchless finger vein recognition.
- Journal of Information Processing Society (B) (2008, in Korean): PDF
Iris Recognition with eyelid localization on a mobile device
We propose a new portable iris recognition system. Because existing portable iris systems use customized embedded processing units, they are limited in ability to expand to other applications, and they have low processing power. To overcome such problems, we propose a new portable iris recognition system consisting of a conventional ultra-mobile personal computer (UMPC), a small universal serial bus (USB) iris camera, and near-infrared (NIR) light illuminators.
- International Journal of Control, Automation and Systems (2010): PDF