• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.787-796
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• 2014

Many mobile robot navigation methods utilize laser scanners, ultrasonic sensors, vision camera, and so on for detecting obstacles and path following. However, human utilizes only vision(e.g. eye) information for navigation. In this paper, we study a mobile robot control method based on only the camera vision. The Gaussian Mixture Model and a shadow removal technology are used to divide the foreground and the background from the camera image. The mobile robot uses a combined CAMSHIFT and KLT feature tracker algorithms based on the information of the foreground to follow a person. The algorithm is verified by experiments where a person is tracked and followed by a robot in a hallway.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2341-2343
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• 2002

This paper describes a vision-based line recognition and control of driving direction for an AGV(autonomous guided vehicle). As navigation guide, black stripe attached on the corridor is used. Binary image of guide stripe captured by a CCD camera is used. For detect the guideline quickly and extractly, we use for variable thresholding algorithm. this low-cost line-tracking system is efficiently using pc-based real time vision processing. steering control is studied through controller with guide-line angle error. This method is tested via a typical agv with a single camera in laboratory environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.1
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• pp.47-59
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• 2014

This paper deals with a vision-based trajectory tracking control system for a quadrotor-type UAV for entertainment purpose in indoor environment. In contrast to outdoor flights that emphasize the autonomy to complete special missions such as aerial photographs and reconnaissance, indoor flights for entertainment require trajectory following and hovering skills especially in precision and stability of performance. This paper proposes a trajectory tracking control system consisting of a motion generation module, a pose estimation module, and a trajectory tracking module. The motion generation module generates a sequence of motions that are specified by 3-D locations at each sampling time. In the pose estimation module, 3-D position and orientation information of a quadrotor is estimated by recognizing a circular ring pattern installed on the vehicle. The trajectory tracking module controls the 3-D position of a quadrotor in real time using the information from the motion generation module and pose estimation module. The proposed system is tested through several experiments in view of one-point, multi-points, and trajectory tracking control.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose an algorithm that can estimate the distance using disparity based on stereo vision system, even though the obstacle is located in long ranges as well as short ranges. We use sub-pixel interpolation to minimize quantization errors which deteriorate the distance accuracy when calculating the distance with integer disparity, and also we use enhanced adaptive fuzzy strong tracking Kalman filter(EAFSTKF) to improve the distance accuracy and track the path optimally. The proposed method can solve the divergence problem caused by nonlinear dynamics such as various vehicle movements in the conventional Kalman filter(CKF), and also enhance the distance accuracy and reliability. Our simulation results show that the performance of our method improves by about 13.5% compared to other methods in point of root mean square error rate(RMSER).

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.274-282
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• 2018

Most occupancy sensors installed in buildings, households and so forth are pyroelectric infra-red (PIR) sensors. One of disadvantages is that PIR sensor can not detect the stationary person due to its functionality of detecting the variation of thermal temperature. In order to overcome this problem, the utilization of camera vision sensors has gained interests, where object tracking is used for detecting the stationary persons. However, the object tracking has an inherent problem such as tracking drift. Therefore, the recognition of humans in static trackers is an important task. In this paper, we propose a CNN-based human recognition to determine whether a static tracker contains humans. Experimental results validated that human and non-humans are classified with accuracy of about 88% and that the proposed method can be incorporated into practical vision occupancy sensors.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.154-158
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• 2002

This paper describes a path tracking method for vision-based and autonomous mobile robot in a corridor. At first, we extract the ceiling-lamp of the corridor through simple preprocessing (gray, thresholding, labeling, etc.) for robot position and orientation. Then, we design the controller for path-tracking. Simulations conducted, and acceptable vehicle localization results were obtained to prove the feasibility of the proposed approach.

• Journal of Sensor Science and Technology
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• v.24 no.1
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• pp.54-61
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• 2015

In recent years, there has been increasing use of automatic surveillance and monitoring systems based on vision sensors. Humans are often the most important target in the systems, but processing human images is difficult due to the small sizes and flexible motions. Particularly, occlusion among pedestrians in camera images brings practical problems. In this paper, we propose a novel method to separate image regions of occluded pedestrians. A camera equipped with a wide angle lens is attached to the ceiling of a building corridor for sensing pedestrians with a wide field of view. The output images of the camera are processed for the human detection, tracking, identification, distortion correction, and occlusion handling. We resolve the occlusion problem adaptively depending on the angles and positions of their heads. Experimental results showed that the proposed method is more efficient and accurate compared with existing methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.295-296
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• 2012

그림 툴은 실시간 비디오 영상 스트림과 트래킹 시스템을 통해 사용자의 손가락 움직임의 입력을 받아 가상의 오브젝트들을 그려서 보여주는 툴이다. 핵심개발기술은 병렬처리언어인 CUDA사용하여 개발된 저가의 비전 기반 트래킹 시스템이다. 저가의 트래킹 시스템과 그림툴의 설계, 구현, 앞으로의 발전 방향에 대해 설명한다.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.862-866
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• 2004

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. Based on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.