Entity

Time filter

Source Type


Lim S.,NHN NEXT | Lee J.,Creative Content Research Laboratory
ETRI Journal | Year: 2013

In recent years, augmented reality (AR) technologies have been the subject of great interest among many communities. In education applications, old-fashioned materials (or textbooks) are still used, despite remarkable AR developments in the industrial area. We present an AR system for education. Our system consists of an authoring tool that can be used to create educational content, a viewer that plays that content, and an engine to manage the tool and viewer. In our system, a marker unit recognizes a marker printed on a plane or a cubic plane by adaptively adjusting the threshold to have an excellent recognition rate in diverse environments and acquires corresponding data of the marker. Based on the system, we test 142 elementary school students for increased educational benefits using our system. © 2013 ETRI.


Kim Y.-G.,Sejong University | Kim H.-J.,Sejong University | Choi I.-H.,Sejong University | Kim J.-S.,Creative Content Research Laboratory | Choi S.-M.,Sejong University
ETRI Journal | Year: 2012

We propose an efficient framework to realistically render 3D faces with a reduced set of points. First, a robust active appearance model is presented to detect facial features in the projected faces under different illumination conditions. Then, an adaptive simplification of 3D faces is proposed to reduce the number of points, yet preserve the detected facial features. Finally, the point model is rendered directly, without such additional processing as parameterization of skin texture. This fully automatic framework is very effective in rendering massive facial data on mobile devices. © 2012 ETRI.


Kim H.,Creative Content Research Laboratory | Lee G.A.,University of Canterbury | Yang U.,Creative Content Research Laboratory | Kwak T.,Korean University of Science and Technology | Kim K.-H.,Creative Content Research Laboratory
ETRI Journal | Year: 2012

In this letter, we propose a dual autostereoscopic display platform employing a natural interaction method, which will be useful for sharing visual data with users. To provide 3D visualization of a model to users who collaborate with each other, a beamsplitter is used with a pair of autostereoscopic displays, providing a visual illusion of a floating 3D image. To interact with the virtual object, we track the user's hands with a depth camera. The gesture recognition technique we use operates without any initialization process, such as specific poses or gestures, and supports several commands to control virtual objects by gesture recognition. Experiment results show that our system performs well in visualizing 3D models in realtime and handling them under unconstrained conditions, such as complicated backgrounds or a user wearing short sleeves. © 2012 ETRI.


Chang J.Y.,Creative Content Research Laboratory | Nam S.W.,Creative Content Research Laboratory
ETRI Journal | Year: 2013

Since the recent launch of Microsoft Xbox Kinect, research on 3D human pose estimation has attracted a lot of attention in the computer vision community. Kinect shows impressive estimation accuracy and real-time performance on massive graphics processing unit hardware. In this paper, we focus on further reducing the computation complexity of the existing state-of-the-art method to make the real-time 3D human pose estimation functionality applicable to devices with lower computing power. As a result, we propose two simple approaches to speed up the random-forest-based human pose estimation method. In the original algorithm, the random forest classifier is applied to all pixels of the segmented human depth image. We first use a multi-scale approach to reduce the number of such calculations. Second, the complexity of the random forest classification itself is decreased by the proposed cascade approach. Experiment results for real data show that our method is effective and works in real time (30 fps) without any parallelization efforts. © 2013 ETRI.


Kim J.,Creative Content Research Laboratory | Jeong I.,Creative Content Research Laboratory
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

In this paper, we present an improved method of current closed-form solution for digital image matting. This method, which we call 'normalized matting of interest region', adopt the normalized cut technique where the objective function is normalized with the total degree of color similarities of foreground region. Unlike the existing solution, our method measures both the total dissimilarity between the foreground and background regions as well as the total similarity within foreground regions, which leads to better separation results, especially in case of extracting a specific region, rather than the closed-form solution. In addition, we employ a quadratic programming approach to solve the objective function to obtain a globally near-optimal matting result. Our method is empirically verified through several sample images. © 2013 Springer-Verlag.

Discover hidden collaborations