• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.157-166
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• 2009

There is a growing interest in ubiquitous-related research and applications. Among them, GPS-based LBS have been developed and used actively. Recently, with the increase of large size buildings and disastrous events, indoor spaces are getting attention and related research activities are being carried out. Core technologies regarding indoor applications may include 3D indoor data modeling and localization sensor techniques that can integrate with indoor data. However, these technologies have not been standardized and established enough to be applied to indoor implementation. Thus, in this paper, we propose a method to build a relatively simple 3D indoor data modeling technique that can be applied to indoor location based applications. The proposed model takes the form of 2D-based multi-layered structure and has capability for 2D and 3D visualization. We tested three prototype applications using the proposed model; CA(cellular automata)-based 3D evacuation simulation, network-based routing, and indoor moving objects tracking using a stereo camera.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.353-358
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• 2022

Due to the limited field of view of the pinhole camera, there is a lack of stability and accuracy in camera pose estimation applications such as visual SLAM. Nowadays, multiple-camera setups and large field of cameras are used to solve such issues. However, a multiple-camera system increases the computation complexity of the algorithm. Therefore, in multiple camera-assisted visual simultaneous localization and mapping (vSLAM) the multi-view tracking algorithm is proposed that can be used to balance the budget of the features in tracking and local mapping. The proposed algorithm is based on PanoSLAM architecture with a panoramic camera model. To avoid the scale issue 3D LiDAR is fused with omnidirectional camera setup. The depth is directly estimated from 3D LiDAR and the remaining features are triangulated from pose information. To validate the method, we collected a dataset from the outdoor environment and performed extensive experiments. The accuracy was measured by the absolute trajectory error which shows comparable robustness in various environments.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1999-2000
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• 2006

기존 2D 추적기들은 영상에서 특정 평면 영역을 원근 투영하에서 만족할 만한 추적결과를 보여주었다. 하지만 2D 추적기는 2D 영역들로 이루어진 3D물체를 영상에서 추적하는 경우, 물체자신의 회전에 의해 가려지거나 새로 나타나는 영역에 대해 대응하지 못하여 추적에 실패하게 되지만, 3D 정보를 이용한다면 이러한 사라짐과 나타나는 영역을 예측하고 완벽하게 추적할 수 있게 된다. 본 연구에서는 일련의 영상으로부터 3D 모델과 2D 텍스쳐맵을 추출하고, 이를 이용하여 3D 물체의 회전과 평행이동 움직임을 추적한다. 또한 카메라의 줌 파라미터를 모델링하고 추적기 알고리즘에 추가하여, 물체의 3차원 파라미터의 추적과 동시에 카메라 줌 파라미터를 추적하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.119-133
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• 2009

The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.79-87
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• 2000

In this paper, we propose a model based moving object tracking algorithm In dynamic scenes To adapt shape change of the moving object, the Hausdorff distance is applied as the measurement of similarity between model and image To reduce processing time, 2D logarithmic search method is applied for locate the position of moving object Experiments on a running vehicle and motorcycle, the result showed that the mean square error of real position and tracking result is 1150 and 1845; matching times are reduced average 1125times and 523 times than existing algorithm for vehicle image and motorcycle image, respectively It showed that the proposed algorithm could track the moving object accurately.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3037-3040
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• 2000

Real-Time object tracking has emerged as an important component in several application areas including machine vision. surveillance. Human-Computer Interaction. image-based control. and so on. And there has been developed various algorithms for a long time. But in many cases. they have showed limited results under uncontrolled situation such as illumination changes or cluttered background. In this paper. we present a novel. computationally efficient algorithm for tracking human face robustly under illumination changes and cluttered backgrounds. Previous algorithms usually defines color model as a 2D membership function in a color space without consideration for illumination changes. Our new algorithm developed here. however. constructs a 3D color model by analysing plenty of images acquired under various illumination conditions. The algorithm described is applied to a mobile head-eye robot and experimented under various uncontrolled environments. It can track an human face more than 100 frames per second excluding image acquisition time.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.107-111
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• 1998

This paper presents a now approach to the design of intelligent contorl system for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. Moreover, We develop a Windows 95 version dynamic simulator which can simulate a track vehicle model in 3D graphics space. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The dynamic simulator for track vehicle is developed by Microsoft Visual C++. Graphic libraries, OpenGL, by Silicon Graphics, Inc. were utilized for 3D Graphics. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.171-177
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• 2015

A telerobot offers a more engaging and enjoyable interaction with people at a distance by communicating via audio, video, expressive gestures, body pose and proxemics. To provide its potential benefits at a reasonable cost, this paper presents a telepresence robot system for video communication which can deliver speaker's head motion through its display stanchion. Head gestures such as nodding and head-shaking can give crucial information during conversation. We also can assume a speaker's eye-gaze, which is known as one of the key non-verbal signals for interaction, from his/her head pose. In order to develop an efficient head tracking method, a 3D cylinder-like head model is employed and the Harris corner detector is combined with the Lucas-Kanade optical flow that is known to be suitable for extracting 3D motion information of the model. Especially, a skin color-based face detection algorithm is proposed to achieve robust performance upon variant directions while maintaining reasonable computational cost. The performance of the proposed head tracking algorithm is verified through the experiments using BU's standard data sets. A design of robot platform is also described as well as the design of supporting systems such as video transmission and robot control interfaces.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.775-778
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• 2008

Augmented Reality is a growing area in virtual reality research, The world environment around us provides a wealth of information that is difficult to duplicate in a computer. This evidenced by the worlds used in virtual environments. An augmented reality system generates a composite view for the user. It is a combination of the real scene viewed by the user and a virtual scene generated by the computer that augments the scene with addition information. The registration method represent to the user enhances that person's performance in and perception of the world. It decide the direction and location between real world and 3D graphic objects. The registration method devide two method, Model based tracking and Move-Matching. This paper researched at to generate a commerce correlation using a tracking object method, using at a color distribution and information, in the sequence scene.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.287-294
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• 2010

TOF technique is one of the skills that can obtain the object's 3D depth information. But depth image has low resolution and fingertip occupy very small region, so, it is difficult to find the precise fingertip's 3D information by only using depth image from TOF camera. In this paper, we estimate fingertip's 3D location using Arm Model and reliable hand's 3D location information that is modified by hexahedron as hand model. Using proposed method we can obtain more precise fingertip's 3D information than using only depth image.