• Journal of Advanced Navigation Technology
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• v.9 no.1
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• pp.48-55
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• 2005

In this paper, we propose an efficient moving object tracking technique for multi-camera surveillance system. Color CCD cameras used in this system are network cameras with their own IP addresses. Input image is transmitted to the media server through wireless connection among server, bridge, and Access Point (AP). The tracking system sends the received images through the network to the tracking module, and it tracks moving objects in real-time using color matching method. We compose two sets of cameras, and when the object is out of field of view (FOV), we accomplish hand-over to be able to continue tracking the object. When hand-over is performed, we use MHI(Motion History Information) based on color information and M-bin histogram for an exact tracking. By utilizing MHI, we can calculate direction and velocity of the object, and those information helps to predict next location of the object. Therefore, we obtain a better result in speed and stability than using template matching based on only M-bin histogram, and we verified this result by an experiment.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.913-919
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• 2016

In this paper, we propose the visual tracking algorithm that takes advantage of multiple random walkers. We first show the tracking method based on support vector machine as [1] and suggest a method that suppresses feature vectors extracted from backgrounds while preserve features vectors from foregrounds. We also show how to discriminate between foregrounds and backgrounds. Learned by reducing influences of backgrounds, support vector machine can clearly distinguish foregrounds and backgrounds from the image whose target objects are similar to backgrounds and occluded by another object. Thus, the algorithm can track target objects well. Furthermore, we introduce a simple method improving tracking speed. Finally, experiments validate that proposed algorithm yield better performance than the state-of-the-art trackers on the widely-used benchmark dataset with high speed.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.618-624
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• 2010

This paper address the problem of tracking multiple objects encountered in many situations in developing condensation algorithms. The difficulty lies on the fact that the implementation of condensation algorithm is not easy for the general users. We propose an automatic code generation program for condensation algorithm using MATLAB tool. It will help for general user who is not familiar with condensation algorithm to apply easily for real system. The merit of this program is that a that a general industrial engineer can easily simulate the designed system and confirm the its performance on the fly.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.697-704
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• 2003

In this paper, the visual tracking system for arbitrary shaped moving object is proposed. The established tracking system can be divided into model based method that needs previous model for target object and image based method that uses image feature. In the model based method, the reliable tracking is possible, but simplification of the shape is necessary and the application is restricted to definite target mod el. On the other hand, in the image based method, the process speed can be increased, but the shape information is lost and the tracking system is sensitive to image noise. The proposed tracking system is composed of the extraction process that recognizes the existence of moving object and tracking process that extracts dynamic characteristics and shape information of the target objects. Specially, active contour model is used to effectively track the object that is undergoing shape change. In initializatio n process of the contour model, the semi-automatic operation can be avoided and the convergence speed of the contour can be increased by the proposed effective initialization method. Also, for the efficient solution of the correspondence problem in multiple objects tracking, the variation function that uses the variation of position structure in image frame and snake energy level is proposed. In order to verify the validity and effectiveness of the proposed tracking system, real time tracking experiment for multiple moving objects is implemented.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.4
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• pp.274-282
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• 2009

Various location tracking sensors; such as GPS, INS, radar, and optical equipment; are used for tracking moving targets. In order to effectively track moving targets, it is necessary to develop an effective fusion method for these heterogeneous devices. There have been studies in which the estimated values of each sensors were regarded as different models and fused together, considering the different error characteristics of the sensors for the improvement of tracking performance using heterogeneous multi-sensor. However, the rate of errors for the estimated values of other sensors has increased, in that there has been a sharp increase in sensor errors and the attempts to change the estimated sensor values for the Sensor Probability could not be applied in real time. In this study, the Sensor Probability is obtained by comparing the RMSE (Root Mean Square Error) for the difference between the updated and measured values of the Kalman filter for each sensor. The process of substituting the new combined values for the Kalman filter input values for each sensor is excluded. There are improvements in both the real-time application of estimated sensor values, and the tracking performance for the areas in which the sensor performance has rapidly decreased. The proposed algorithm adds the error characteristic of each sensor as a conditional probability value, and ensures greater accuracy by performing the track fusion with the sensors with the most reliable performance. The trajectory of a UAV is generated in an experiment and a performance analysis is conducted with other fusion algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.781-784
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• 2004

본 시스템은 어항속에 있는 물고기 움직임을 추적하기 위해 두 대의 카메라로부터 동시에 독립된 영상을 획득하고 획득된 영상을 처리하여 좌표를 얻어내고 3차원 좌표로 생성해내는 시스템이다. 제안하는 방법은 크게 두 대의 카메라로부터 동시에 영상을 획득하는 방법과 획득된 영상에 대한 처리 및 물체 위치 검출, 그리고 3차원 좌표 생성으로 구성된다. Frame grabber를 사용하여 두 개의 카메라로부터 동시에 영상을 획득하며, 3개의 연속된 프레임에 대한 차영상과 ART2(Adaptive Resonance Theory)를 이용하여 각각의 영상에서의 물고기 위치를 검출한다. 검출된 각각의 좌표를 병합하여 3차원 좌표를 생성하며, 추적 결과는 OpenGL을 이용하여 3차원으로 재생한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.415-418
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• 2007

가까운 미래에 인간생활에 활용될 지능형 로봇은 인간과 공존하면서도 효과적으로 인간을 도와줄 수 있는 인간친화형 로봇이라 할 수 있다. 이러한 것을 실현하기 위해서 로봇은 미지의 환경 내에서 자신의 위치 및 방향을 인식해야 할 필요가 있다. 더욱이, 이것은 일상생활에서 자연스럽게 이뤄지는 것이 당연하다. 로봇을 제어하는 가장 중요한 문제중의 하나로서 이동로봇의 주행에서의 위치불확실성을 해결함으로서 로봇의 위치를 추정하는 것이 바람직하다 할 수 있다. 본 논문에서는 실내외 공간에서 인간을 포한함 이동물체의 영상정보를 이용하여 이동로봇의 자기위치를 인식하기 위한 방법을 제시하고 있다. 제시한 방법은 로봇자체의 DR센서 정보와 카메라에서 얻은 영상정보로부터 로봇의 위치추정방법을 결합 한 것이다. 그리고 이동물체의 이전 위치정보와 관측 카메라의 모델을 사용하여 이동물체에 대한 영상프레임 좌표와 추정된 로봇위치 간의 관계를 표현할 수 있는 식을 제시하고 있다. 또한 이동하는 인간과 로봇의 위치와 방향을 추정하기 위한 제어방법을 제시하고 이동로봇의 위치를 추정하기위해서 칼만필터 방법을 적용하였다. 그리고 시뮬레이션 및 실험을 통하여 제시한 방법을 검증하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.91-93
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• 2016

From the 2-D image extracting three-dimensional information as the latter is in the bilateral sibeop using two camera method and when using a monocular camera as a very important step generally as "stereo vision". There in today's CCTV and automatic object tracking system used in many medium much to know the site conditions or work developed more clearly by using a stereo camera that mimics the eyes of humans to maximize the efficiency of avoidance / control start and multiple jobs can do. Object tracking system of the existing 2D image will have but can not recognize the distance to the transition could not be recognized by the observer display using a parallax of a stereo image, and the object can be more effectively controlled.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.105-115
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• 2017

Conventional traffic detection sensors such as loop detectors and image sensors are expensive to install and maintain and require different detection algorithms depending on the night and day and have a disadvantage that the detection rate varies widely depending on the weather. On the other hand, the millimeter-wave radar is not affected by bad weather and can obtain constant detection performance regardless of day or night. In addition, there is no need for blocking trafficl for installation and maintenance, and multiple vehicles can be detected at the same time. In this study, a multi-target detection algorithm for a radar sensor with this advantage was devised / implemented by applying a conventional single target detection algorithm. We performed the evaluation and the meaningful results were obtained.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.2
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• pp.127-136
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• 2016

The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.