• Proceedings of the Korean Information Science Society Conference
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• 2010.06b
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• pp.227-230
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• 2010

비젼 기반의 휴먼 인체 추적 문제는 추정해야 할 파라미터의 수가 많고, 인체 구성 요소들 간의 가려짐등으로 인해 발생하는 포즈 간의 모호성 등으로 야기되는 어려움을 가지고 있다. 본 논문에서는 다양한 휴먼 상체 포즈에 따른 고차원 탐색 공간을 효율적으로 계산할 수 있는 Mean-Shift Belief Propagation (MSBP) 및 역기구학(Inverse Kinematics) 제약에 기반한 방법을 제안한다. 제안된 방법의 효율성을 증명하기 위해 실험을 기존에 제안된 방법들과의 비교 실험을 수행하였다.

• Journal of Power System Engineering
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• v.6 no.1
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• pp.96-101
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• 2002

In this paper, we address the problem of controlling an end-effector to track and grab a moving target using the visual servoing technique. A visual servo mechanism based on the image-based servoing principle, is proposed by using visual feedback to control an end-effector without calibrated robot and camera models. Firstly, we consider the control problem as a nonlinear least squares optimization and update the joint angles through the Taylor Series Expansion. And to track a moving target in real time, the Jacobian estimation scheme(Dynamic Broyden's Method) is used to estimate the combined robot and image Jacobian. Using this algorithm, we can drive the objective function value to a neighborhood of zero. To show the effectiveness of the proposed algorithm, simulation results for a six degree of freedom robot are presented.

• Annual Conference of KIPS
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• 2013.11a
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• pp.1321-1323
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• 2013

지능형 자동차에서 영상 기반 능동 안전시스템의 신뢰성을 확보하기 위해서는 도로 위의 다양한 객체를 강건하게 검출하고, 추적하는 것이 가장 중요하다. 본 논문에서는 다중 가설 기반 추적 프레임워크를 이용하여, 실시간으로 전방 차량을 검출하고 추적하는 시스템을 제안한다. 제안한 시스템은 다양한 외부 도로 환경에서 획득된 실험 영상에 대하여 10-15Hz 의 처리 속도로, 평균적으로 98%의 인식률을 제공할 수 있다.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1145-1156
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• 2002

A method to measure the speed and distance of moving object is proposed using the stereo vision system. One of the most important factors for measuring the speed and distance of moving object is the accuracy of object tracking. Accordingly, the background image algorithm is adopted to track the rapidly moving object and the local opening operator algorithm is used to remove the shadow and noise of object. The extraction efficiency of moving object is improved by using the adaptive threshold algorithm independent to variation of brightness. Since the left and right central points are compensated, the more exact speed and distance of object can be measured. Using the background image algorithm and local opening operator algorithm, the computational processes are reduced and it is possible to achieve the real-time processing of the speed and distance of moving object. The simulation results show that background image algorithm can track the moving object more rapidly than any other algorithm. The application of adaptive threshold algorithm improved the extraction efficiency of the target by reducing the candidate areas. Since the central point of the target is compensated by using the binocular parallax, the error of measurement for the speed and distance of moving object is reduced. The error rate of measurement for the distance from the stereo camera to moving object and for the speed of moving object are 2.68% and 3.32%, respectively.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.61-67
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• 2017

Recently, CCTV has been combined with areas such as big data, artificial intelligence, and image analysis to detect various abnormal behaviors and to detect and analyze the overall situation of objects such as people. Image analysis research for this intelligent video surveillance function is progressing actively. However, CCTV images using 2D information generally have limitations such as object misrecognition due to lack of topological information. This problem can be solved by adding the depth information of the object created by using two cameras to the image. In this paper, we perform background modeling using Mixture of Gaussian technique and detect whether there are moving objects by segmenting the foreground from the modeled background. In order to perform the depth information-based segmentation using the RGB information-based segmentation results, stereo-based depth maps are generated using two cameras. Next, the RGB-based segmented region is set as a domain for extracting depth information, and depth-based segmentation is performed within the domain. In order to detect the center point of a robustly segmented object and to track the direction, the movement of the object is tracked by applying the CAMShift technique, which is the most basic object tracking method. From the experiments, we prove the efficiency of the proposed object detection and tracking method using the RGB-D model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.246-253
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• 2010

In this paper, a method of removing the space skew and cross-talk cancellation is proposed where the self-generated signals from the subject are used to obtain the subject's location. In the proposed method, the good spatial sound image is maintained even when the listener moves from the sweet spot. Two major parts of the proposed method are as follows: listener position tracking using the stimuli from the subject and removal of the space skew and cross-talk signals. Listener position tracking is achieved by estimation of the time difference of arrival (TDoA). The position of the listener is then computed using the Talyer-series estimation method. The head-related transfer functions (HRTF) are used to remove the space skew and cross-talk signals, where the direction of the HRTF is given by the one estimated from the listener position tracking. The performance evaluation is carried out on the signals from the 100 subjects that are composed of the 50 female and 50 male subjects. The positioning accuracy is achieved by 70%~90%, under the condition that the mean squared positioning error is less than $0.07m^2$. The subjective listening test is also conducted where the 27 out of the 30 subjects are participated. According to the results, 70% of the subjects indicates that the overall quality of the reproduced sound from the proposed method are improved, regardless of the subject's position.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2C
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• pp.112-118
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• 2011

In this paper, we conduct an objective performance analysis of the crosstalk cancellation scheme studied in [11]. While the conventional scheme is only applicable to a listener on the optimal listenable region (sweetspot), the space skew/crosstalk cancellation (SS/CC) scheme in [11] can mitigate crosstalk regardless of the listener's position by using listener position tracking (LPT) system. The SS/CC scheme is composed of two parts: LPT-based SS and CC parts. In this paper, the SS/CC scheme is evaluated by some criteria such as follows: condition number, and the balance characteristic, its root mean square error, and running average.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.705-713
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• 2009

This paper proposes CORBA-based visual servoing system of humanoid robot. To effectively control the humanoid robot which is connected to network, it needs to define necessary services for visual servoing as distribution object, and realize them in the middleware. For realizing it following services should be addressed. Naming service for searching a necessary service with unique name assigned to each object, image service for supplying image obtained from stereo camera. In the experiment, we show the result of balloon tracking and bursting that the robot tracks balloons as target objects in the real time, and if a balloon stop for a certain time, then the robot bursts the balloon.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.6
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• pp.134-140
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• 2008

Preceding vehicle detection is a crucial issue for driver assistance system as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision. The vision-based preceded vehicle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an preceded vehicle detection system is developed using stereo vision sensors. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the preceded vehicles including a leading vehicle. Then, the position parameters of the preceded vehicles or leading vehicles can be obtained. The proposed preceded vehicle detection system is implemented on a passenger car and its performances is verified experimentally.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.595-601
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• 2011

This paper presents balancing control of inverted pendulum on the ROBOKER arm using visual information. The angle of the inverted pendulum placed on the robot arm is detected by a stereo camera and the detected angle is used as a feedback and tracking error for the controller. Thus, the overall closed loop forms a visual servoing control task. To improve control performance, neural network is introduced to compensate for uncertainties. The learning algorithm of radial basis function(RBF) network is performed by the digital signal controller which is designed to calculate floating format data and embedded on a field programmable gate array(FPGA) chip. Experimental studies are conducted to confirm the performance of the overall system implementation.