• Journal of Astronomy and Space Sciences
• /
• v.20 no.2
• /
• pp.153-162
• /
• 2003

Recently, we have reconstructed LX-200 12inch telescope system for tracking and observing man-made space object. Motor, motor driver and motion controller were up-graded for getting faster respond characteristic and active control available. Also, command signal was offered to the PID controller into motor driver as computed real orbiting information of objects using PC, and it's control period of command signal was reduced to the 20ms. As the result, slew speed of the mount system was in proved up to $18^{\circ}/sec$ and respond speed of the system was faster than that of commercial system. Also, flipping state of image observed could be minimized by the up-graded system.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.40 no.2
• /
• pp.118-128
• /
• 2012

The goal of this paper is to design the target tracking controller for a quadrotor micro UAV using a vision sensor. First of all, the mathematical model of the quadrotor was estimated through the Prediction Error Method(PEM) using experimental input/output flight data, and then the estimated model was validated via the comparison with new experimental flight data. Next, the target tracking controller was designed using LQR(Linear Quadratic Regulator) method based on the estimated model. The relative distance between an object and the quadrotor was obtained by a vision sensor, and the altitude was obtained by a ultra sonic sensor. Finally, the performance of the designed target tracking controller was evaluated through flight tests.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.23 no.8
• /
• pp.1998-2009
• /
• 1998

An effective algorithm for tracking rigid or non-rigid moving object(s) which segments local moving parts from image sequence in the presence of backgraound motion by camera movenment, predicts the direction of it, and tracks the object is proposed. It requires no camera calibration and no knowledge of the installed position of camera. In order to segment the moving object, feature points configuring the shape of moving object are firstly selected, feature flow field composed of motion vectors of the feature points is computed, and moving object(s) is (are) segmented by clustering the feature flow field in the multi-dimensional feature space. Also, we propose IRMAS, an efficient algorithm that finds the convex hull in order to cinstruct the shape of moving object(s) from clustered feature points. And, for the purpose of robjst tracking the objects whose movement characteristics bring about the abrupt change of moving trajectory, an improved order adaptive lattice structured linear predictor is used.

• International Journal of Aeronautical and Space Sciences
• /
• v.15 no.3
• /
• pp.258-266
• /
• 2014

We present a system for the real-time visual relative navigation of a fixed-wing unmanned aerial vehicle in a GPS-denied environment. An extended Kalman filter is used to construct a vision-aided navigation system by fusing the image processing results with barometer and inertial sensor measurements. Using a mean-shift object tracking algorithm, an onboard vision system provides pixel measurements to the navigation filter. The filter is slightly modified to deal with delayed measurements from the vision system. The image processing algorithm and the navigation filter are verified by flight tests. The results show that the proposed aerial system is able to maintain circling around a target without using GPS data.

• International Journal of Aeronautical and Space Sciences
• /
• v.14 no.3
• /
• pp.282-295
• /
• 2013

In order to communicate with a ground station, the tracking profile design problem for a directional antenna system is considered. Because the motions of the gimbal angles in the antenna system affect the image quality, the main object is to minimize the motion of the gimbal angles during the satellite's imaging phase. For this goal, parameter optimization problems in the imaging and maneuver phases are formulated separately in the body-frame, and solved sequentially. Also, several mechanical constraints, such as the limitation of the gimbal angle and rate, are considered in the problems. The tracking profiles of the gimbal angles in the maneuver phases are designed with N-th order polynomials, to continuously connect the tracking profiles between two imaging phases. The results confirm that if the vector trace of the desired antenna-pointing vector is within the antenna's beam-width angle, motions of the gimbal angles are not required in the corresponding imaging phase. Also, through numerical examples, it is shown that motion of the gimbal angles in the imaging phase can be minimized by the proposed design process.

• Proceedings of the Korean Information Science Society Conference
• /
• 2000.04b
• /
• pp.487-489
• /
• 2000

본 논문에서는 다해상도 영상에서 움직이는 다중 객체의 추적 방법을 다룬다. 일반적으로 객체 추적 알고리즘은 움직임 탐지, 정합, 갱신의 처리 단계로 구성되어 있다. 특히 다중객체 추적일 경우, 정합 과정은 매우 중요하다. 일반적인 시각 시스템에서는 대상 객체가 강체(rigid object)라고 가정하면 이러한 정합 과정은 비교적 쉽게 구현될 수 있다. 그러나 다해상도 영상에서는 한 위치에서 다른 위치로 움직일 때 그 영역의 형태 및 크기가 변형 되기 때문에 정합이 쉽게 이루어지지 않는다. 따라서 본 논문에서는 이러한 문제를 해결할 수 있는 다해상도 영상에서의 정합방법을 제안한다.

• The Journal of Engineering Research
• /
• v.6 no.2
• /
• pp.109-117
• /
• 2004

In this paper, we propose an object contour tracking algorithm using snakes in stereo image sequences. The proposed technique is composed of two steps. In the first step, the candidate Snake points are determined from the motion information in 3-D disparity space. In the second step, the energy of Snake function is calculated to check whether the candidate Snake points converge to the edges of the interested objects. The energy of Snake function is calculated from the candidate Snake points using the disparity information obtained by patch matching. The performance of the proposed technique is evaluated by applying it to various sample images. Results prove that the proposed technique can track the edges of objects of interest in the stereo image sequences even in the cases of complicated background images or additive components.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.12
• /
• pp.1033-1041
• /
• 2003

A new visual tracking scheme is proposed for a mobile robot that tracks a moving object in 3D space in real time. Visual tracking is to control a mobile robot to keep a moving target at the center of input image at all time. We made it possible by simplifying the relationship between the 2D image frame captured by a single camera and the 3D workspace frame. To precisely calculate the input vector (orientation and distance) of the mobile robot, the speed vector of the target is determined by eliminating the speed component caused by the camera motion from the speed vector appeared in the input image. The problem of temporary disappearance of the target form the input image is solved by selecting the searching area based on the linear prediction of target motion. The experimental results have shown that the proposed scheme can make a mobile robot successfully follow a moving target in real time.

• The Journal of Korea Robotics Society
• /
• v.5 no.3
• /
• pp.262-269
• /
• 2010

This paper presents a probabilistic head tracking method, mainly applicable to face recognition and human robot interaction, which can robustly track human head against various variations such as pose/scale change, illumination change, and background clutters. Compared to conventional particle filter based approaches, the proposed method can effectively track a human head by regularizing the sample space and sequentially weighting multiple visual cues, in the prediction and observation stages, respectively. Experimental results show the robustness of the proposed method, and it is worthy to be mentioned that some proposed probabilistic framework could be easily applied to other object tracking problems.

• Journal of Korea Society of Industrial Information Systems
• /
• v.16 no.4
• /
• pp.87-98
• /
• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.