• Journal of Convergence for Information Technology
• /
• v.11 no.1
• /
• pp.20-27
• /
• 2021

Eye tracking is one of the NUI technologies, and it finds out where the user is gazing. This technology allows users to input text or control GUI, and further analyzes the user's gaze so that it can be applied to commercial advertisements. In the eye tracking system, the allowable range varies depending on the quality of the image and the degree of freedom of movement of the user. Therefore, there is a need for a method of estimating the accuracy of eye tracking in advance. The accuracy of eye tracking is greatly affected by how the eye tracking algorithm is implemented in addition to hardware variables. Accordingly, in this paper, we propose a method to estimate how many degrees of gaze changes when the pupil center moves by one pixel by estimating the maximum possible movement distance of the pupil center in the image.

• Journal of the Korean Society of Industry Convergence
• /
• v.18 no.2
• /
• pp.82-89
• /
• 2015

This study proposes a new approach to design and control for autonomous mobile robots. In this paper, we describes a fuzzy logic based visual servoing system for an autonomous mobile robot. An existing system always needs to keep a moving object in overall image. This mes difficult to move the autonomous mobile robot spontaneously. In this paper we first explain an autonomous mobile robot and fuzzy logic system. And then we design a fuzzy logic based visual servoing system. We extract some features of the object from an overall image and then design a fuzzy logic system for controlling the visual servoing system to an exact position. We here introduce a shooting robot that can track an object and hit it. It is illustrated that the proposed system presents a desirable performance by a computer simulation and some experiments.

• Journal of Korea Multimedia Society
• /
• v.9 no.4
• /
• pp.470-481
• /
• 2006

In this paper, we propose a real-time face detection, tracking and tilted face image correction system using multi-color model and face feature information. In the proposed system, we detect face candidate using YCbCr and YIQ color model. And also, we detect face using vertical and horizontal projection method and track people's face using Hausdorff matching method. And also, we correct tilted face with the correction of tilted eye features. The experiments have been performed for 110 test images and shows good performance. Experimental results show that the proposed algorithm robust to detection and tracking of face at real-time with the change of exterior condition and recognition of tilted face. Accordingly face detection and tilted face correction rate displayed 92.27% and 92.70% respectively and proposed algorithm shows 90.0% successive recognition rate.

• Journal of Information Display
• /
• v.3 no.2
• /
• pp.19-25
• /
• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.1 no.3
• /
• pp.111-117
• /
• 2008

Presentation with a projector and a laser pointer is widely used in seminar or conference. The function of a laser pointer in the presentation is just indicating a certain object. In this paper, to give a mouse-like function to a laser pointer, we implement a system that locates the track of a laser pointer. The system contains a FPGA that implements camera interface and noise filter. A software for ARM processor is programmed to analyze the spectrum of the captured image and track the pattern of a laser pointer with previously stored image. As a result, the tracking system could locate the position correctly most of time within 20m with 98% accuracy.

• Journal of Broadcast Engineering
• /
• v.24 no.2
• /
• pp.243-250
• /
• 2019

In this paper, we propose a system for processing and analyzing drone image information which can be applied variously in disasters-security situation. The proposed system stores the images acquired from the drones in the server, and performs image processing and analysis according to various scenarios. According to each mission, deep-learning method is used to construct an image analysis system in the images acquired by the drone. Experiments confirm that it can be applied to traffic volume measurement, suspect and vehicle tracking, survivor identification and maritime missions.

• Journal of information and communication convergence engineering
• /
• v.8 no.4
• /
• pp.466-471
• /
• 2010

We have proposed a method to detect and track moving ships using position from Radar and image processor. Real-time segmentation of moving regions in image sequences is a fundamental step in the radar-camera integrated system. Algorithms for segmentation of objects are implemented by composing of background subtraction, morphologic operation, connected components labeling, region growing, and minimum enclosing rectangle. Once the moving objects are detected, tracking is only performed upon pixels labeled as foreground with reduced additional computational burdens.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.77.4-77
• /
• 2001

The quality of agricultural products is classified with various factors which are measured and determined by destructive and/or nondestructive method. NIR spectrum analysis method is used to determine internal qualities such as a brix and an acidity. CCD color camera is used to measure external quality like color and a size of fruit. today, nondestructive methods are widely researched. The quality and the garde of fruit loaded into a cup automatically and measured in real time by camera and NIR system is determined by internal and external factors. This paper proposes modified boundary tracking algorithm which detects the contour of fruit´s color image and make chain code faster than conventional method ...

• Journal of Korea Multimedia Society
• /
• v.18 no.5
• /
• pp.610-619
• /
• 2015

*In this paper, we propose a real-time face tracking system using an adaptive face detector and a tracking algorithm. An image is divided into the regions of background and face candidate by a real-time updated skin color identifying system in order to accurately detect facial features. The facial characteristics are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted by Principal Component Analysis (PCA), and the interpreted principal components are processed by Support Vector Machine (SVM) that classifies into facial and non-facial areas. The movement of the face is traced by Kalman filter and Mean shift, which use the static information of the detected faces and the differences between previous and current frames. The proposed system identifies the initial skin color and updates it through a real-time color detecting system. A similar background color can be removed by updating the skin color. Also, the performance increases up to 20% when the background color is reduced in comparison to extracting features from the entire region. The increased detection rate and speed are acquired by the usage of Kalman filter and Mean shift.