• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.239-244
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• 2010

This paper is to present map building of mobile robot using RFID (Radio Frequency Identification) technology and ultrasonic sensor. For mobile robot to perform map building, the mobile robot needs its localization and accurate driving in space. In this reason, firstly, kinematic modeling of mobile robot under non-holonomic constrains is introduced. Secondly, based on this modeling, a tracking controller is designed for tracking a given path based on backstepping method using Lyapunov function. The Lyapunov function is also introduced for proving the stability of the designed tracking controller. Thirdly, 2D map building is performed by RFID system, mobile robot system and ultrasonic sensors. The RFID mobile robot system is composed of DC motor, encoder, ultra sonic sensor, digital compass, RFID receiver and RFID antenna. Finally, the path tracking simulation results and map building experimental results are presented to show the effectiveness of the designed controller.

• ETRI Journal
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• v.28 no.3
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• pp.367-370
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• 2006

This letter presents a multi-modal approach to tracking geographic objects such as buildings and road signs in a video sequence recorded from a moving vehicle. In the proposed approach, photogrammetric techniques are successfully combined with conventional tracking methods. More specifically, photogrammetry combined with positioning technologies is used to obtain 3-D coordinates of chosen geographic objects, providing a search area for conventional feature trackers. In addition, we present an adaptive window decision scheme based on the distance between chosen objects and a moving vehicle. Experimental results are provided to show the robustness of the proposed approach.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.3
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• pp.265-272
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• 2019

For tracking a varying number of people using laser range finder, it is important to deal with appearance/disappearance of people due to various causes including occlusions. We propose a method for tracking people with automatic initialization by integrating observations from laser range finder. In our method, the problem of estimating 2D positions and orientations of multiple people's walking direction is formulated based on a mixture kalman filter. Proposal distributions of a kalman filter are constructed by using a mixture model that incorporates information from a laser range scanner. Our experimental results demonstrate the effectiveness and robustness of our method.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.2
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• pp.67-77
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• 2008

Representation of various types of information in an interactive virtual reality environment on mobile devices had been an attractive and valuable research in this new era. Our main focus is presenting spatial indoor location sensing information in 3D perception in mind to replace the traditional 2D floor map using handheld PDA. Designation of 3D virtual reality by Virtual Reality Modeling Language (VRML) demonstrates its powerful ability in providing lots of useful positioning information for PDA user in real-time situation. Furthermore, by interpolating portal culling algorithm would reduce the 3D graphics rendering time on low power processing PDA significantly. By fully utilizing the CC2420 chipbased sensor nodes, wireless sensor network was established to locate user position based on Received Signal Strength Indication (RSSI) signals. Implementation of RSSI-based indoor tracking method is low-cost solution. However, due to signal diffraction, shadowing and multipath fading, high accuracy of sensing information is unable to obtain even though with sophisticated indoor estimation methods. Therefore, low complexity and flexible accuracy refinement algorithm was proposed to obtain high precision indoor sensing information. User indoor position is updated synchronously in virtual reality to real physical world. Moreover, assignment of magnetic compass could provide dynamic orientation information of user current viewpoint in real-time.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.502-506
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• 2010

An augmented book is an application that augments such multimedia elements as virtual 3D objects generated by computer graphics, movie clips, or sound clips to a real book using AR technologies. It is intended to bring additional education and entertainment effects to users. For augmented books, this paper proposes an adaptive keyframe-based page tracking method to estimate the camera's 6 DOF pose in real-time after recognizing a page and performing wide-baseline keypoint matching. For a page tracking, proposed method in this paper chooses a proper keyframe and performs a tracking in two step of coarse-to-fine stage. As a result, the proposed method in this paper guarantees a robust tracking to view-point and illumination variations and real-time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.247-253
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• 2019

In this paper, we present a new method for real-time tracking of human walking around a laser sensor system. The method converts range data with $r-{\theta}$ coordinates to a 2D image with x-y coordinates. Then human tracking is performed using human's features, i.e. appearances of human walking pattern, and the input range data. The laser sensor based human tracking method has the advantage of simplicity over conventional methods which extract human face in the vision data. In our method, the problem of estimating 2D positions and orientations of two walking human's ankle level is formulated based on a moving trajectory algorithm. In addition, the proposed tracking system employs a HMM to robustly track human in case of occlusions. Experimental results using a real system demonstrate usefulness of the proposed method.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.250-256
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• 2009

This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1121-1141
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• 2020

We propose a robust visual object tracking algorithm fusing a convolutional neural network tracker trained offline from a large number of video repositories and a color histogram based tracker to track objects for mixing immersive audio. Our algorithm addresses the problem of occlusion and large movements of the CNN based GOTURN generic object tracker. The key idea is the offline training of a binary classifier with the color histogram similarity values estimated via both trackers used in this method to opt appropriate tracker for target tracking and update both trackers with the predicted bounding box position of the target to continue tracking. Furthermore, a histogram similarity constraint is applied before updating the trackers to maximize the tracking accuracy. Finally, we compute the depth(z) of the target object by one of the prominent unsupervised monocular depth estimation algorithms to ensure the necessary 3D position of the tracked object to mix the immersive audio into that object. Our proposed algorithm demonstrates about 2% improved accuracy over the outperforming GOTURN algorithm in the existing VOT2014 tracking benchmark. Additionally, our tracker also works well to track multiple objects utilizing the concept of single object tracker but no demonstrations on any MOT benchmark.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2701-2706
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• 2003

This paper describes weld seam tracking and error compensation methods of automatic plasma arc welding system designed for the corrugation panel that consists of a linear section and a curved section with various curvatures. Realizing automatic welding system, we are faced with two problems. One is a precise seam tracking and the other is an arc length control. Due to the complexity of the panel shape, it is difficult to find a seam and operate a torch manually in the welding process. So, laser vision sensor for seam tracking is equipped for sensing the seam position and controlling the height of a torch automatically. To attain more precise measurement of an arc length, we measure the 3D shape of the panel and analyze error factors according to the various panel states and caused errors are predicted through the welding process. Using that result, compensation algorithm is added to that of arc length control and real time error compensation is achieved. The result shows that these two methods work effectively.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1377-1381
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• 2003

This paper describes real time object tracking of 3D objects in 2D image sequences. The moving objects are segmented from the image sequence using morphological operations. The moving objects are segmented by the method of differential image followed by the process of morphological dilation. The moving objects are recognized and tracked using statistical moments. The direction of moving objects are determined by the Hough transform. The straight lines in the moving objects are found with the help of Hough transform. The direction of the moving object is calculated from the orientation of the straight lines in the direction of the principal axes of the moving objects. The direction of the moving object and the displacement of the object in the image sequence is used to calculate the velocity of the moving objects. The simulation results of the proposed method are promising on the test images.