• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.454-460
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• 2020

In recent years, the rapid increases in video distribution and viewing over the Internet have increased the risk of personal information exposure. In this paper, a method is proposed to robustly identify areas in images where a person's privacy is compromised and simultaneously blocking the object area by blurring it while rapidly tracking it using a prediction algorithm. With this method, the target object area is accurately identified using artificial neural network-based learning. The detected object area is then tracked using a location prediction algorithm and is continuously blocked by blurring it. Experimental results show that the proposed method effectively blocks private areas in images by blurring them, while at the same time tracking the target objects about 2.5% more accurately than another existing method. The proposed blocking method is expected to be useful in many applications, such as protection of personal information, video security, object tracking, etc.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.2
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• pp.195-201
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• 2005

This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks (GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.157-164
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• 2015

The existing input device is limited to keyboard and mouse. However, recently new type of input device has been developed in response to requests from users. To reflect this trend we propose the new type of input device that gives instruction as analyzing the hand motion of image without special device. After binarizing the skin color area using Cam-Shift method and tracking, it recognizes the hand motion by inputting the finger areas and the angles from the palm center point, which are separated through labeling, into four cardinal directions and counting them. In cases when specific background was not set and without gloves, the recognition rate remained approximately at 75 percent. However, when specific background was set and the person wore red gloves, the recognition rate increased to 90.2 percent due to reduction in noise.

• Korean Institute of Interior Design Journal
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• v.23 no.1
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• pp.122-131
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• 2014

This study aimed to conduct an eye-tracking experiment carried with facade images as a medium and to do research on 'the interest of the eyes' resulted from people's gazing phenomena. This study secured gazing data which appeared according to visual response and analyzed gazing phenomena to find the basic theory of 'the interest of the eyes' as a methodological role, which consumer interest and attention could be grafted when a plan and a design for space design was made. Data terms used in eye-tracking backgrounds and the movement of the eyes were investigated in literature review. Twenty (20) facade images were selected through a case study to get experimental stimuli for the related experiment. Thirty (30) subjects (men and women) suitable for the experiment were recruited to conduct an eye-tracking experiment. After the experiment, five (5) areas were set up in the facade image to identify the focus level of interest and attention. The level of interest and focus was connected to the interest of the eyes. The analysis to study the interest of the eyes was based on nine (9) items such as sequence, entry time, dwell time, hit ratio, revisits, revisitors, average fixation, first fixation and fixation count. Through gaze analysis, the following conclusion was drawn about the 'interest level of sight' for gaze frequency. The interest level can be interpreted to be higher for faster sequence, shorter entry time, longer all fixation(ms) for dwell time, faster all saccade(%), higher hit ratio, more revisits, more revisitors, longer average fixation, faster and longer first fixation, and more fixation count, and the person can be said to have felt interest faster and/or more.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.39-46
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• 2007

Research on human identification in ubiquitous environment has recently attracted a lot of attention. As one of those research, gait recognition is an efficient method of human identification using physical features of a walking person at a distance. In this paper, we present a human shape extraction and tracking for gait recognition using geodesic active contour models(GACMs) combined with mean shift algorithm The active contour models (ACMs) are very effective to deal with the non-rigid object because of its elastic property. However, they have the limitation that their performance is mainly dependent on the initial curve. To overcome this problem, we combine the mean shift algorithm with the traditional GACMs. The main idea is very simple. Before evolving using level set method, the initial curve in each frame is re-localized near the human region and is resized enough to include the targe region. This mechanism allows for reducing the number of iterations and for handling the large object motion. The proposed system is composed of human region detection and human shape tracking modules. In the human region detection module, the silhouette of a walking person is extracted by background subtraction and morphologic operation. Then human shape are correctly obtained by the GACMs with mean shift algorithm. In experimental results, the proposed method show that it is extracted and tracked efficiently accurate shape for gait recognition.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.4
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• pp.345-354
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• 2014

In this paper, we propose a real-time algorithm for estimating the relative position and velocity of a person with respect to a robot using a Kinect sensor and an extended Kalman filter (EKF). Additionally, we propose an algorithm for controlling the robot in the proximity of a person in a variety of modes. The algorithm detects the head and shoulder regions of the person using a histogram of oriented gradients (HOG) and a support vector machine (SVM). The EKF algorithm estimates the relative positions and velocities of the person with respect to the robot using data acquired by a Kinect sensor. We tested the various modes of proximity movement for a human in indoor situations. The accuracy of the algorithm was verified using a motion capture system.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1293-1305
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• 2005

In this paper, we propose the method of manipulating the gaze direction of 3D FPS game's character by using eye gaze detection from the successive images captured by USB camera, which is attached beneath HMD. The proposed method is composed of 3 parts. In the first fart, we detect user's pupil center by real-time image processing algorithm from the successive input images. In the second part of calibration, the geometric relationship is determined between the monitor gazing position and the detected eye position gazing at the monitor position. In the last fart, the final gaze position on the HMB monitor is tracked and the 3D view in game is control]ed by the gaze position based on the calibration information. Experimental results show that our method can be used for the handicapped game player who cannot use his (or her) hand. Also, it can increase the interest and immersion by synchronizing the gaze direction of game player and that of game character.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.703-709
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• 2015

In this work, a robot aimed at grapping and delivering an object by using a simple finger-pointing command from a hand- or arm-handicapped person is introduced. In this robot system, a Leap Motion sensor is utilized to obtain the finger-motion data of the user. In addition, a Kinect sensor is also used to measure the 3D (Three Dimensional)-position information of the desired object. Once the object is pointed at through the finger pointing of the handicapped user, the exact 3D information of the object is determined using an image processing technique and a coordinate transformation between the Leap Motion and Kinect sensors. It was found that the information obtained is transmitted to the robot controller, and that the robot eventually grabs the target and delivers it to the handicapped person successfully.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.313-320
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• 2019

One of the causes of many damage cases that occur today by hacking attack is social engineering attack. The attacker is usually a malicious traitor or an ignorant insider. As a solution, we are strengthening security training for all employees in the organization. Nevertheless, there are frequent situations in which computers are shared. In this case, the person in charge of the computer has difficulty in tracking and responding when a specific representative accessed and what a specific representative did. In this paper, we propose the method that the person in charge of the computer tracks in real time through the smartphone when a representative access the computer, when a representative access offline using hacked or shared authentication. Also, we propose a method to prevent the leakage of important information by encrypting and backing up important files of the PC through the smartphone in case of abnormal access.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.77-84
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• 2021

In this paper, we propose a system that uses image data and beacon data to classify authorized and unauthorized perosn who are allowed to enter a group facility. The image data collected through the IP camera uses YOLOv4 to extract a person object, and collects beacon signal data (UUID, RSSI) through an application to compose a fingerprinting-based radio map. Beacon extracts user location data after CNN-LSTM-based learning in order to improve location accuracy by supplementing signal instability. As a result of this paper, it showed an accuracy of 93.47%. In the future, it can be expected to fusion with the access authentication process such as QR code that has been used due to the COVID-19, track people who haven't through the authentication process.