• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.129-135
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• 2004

In the home health management system, we often face the situation to handle biological signals that are frequently measured from normal subjects. In such a case, it is necessary to decide whether the signal at a certain moment is normal or abnormal. Since ECC is one of the most frequently measured biological signals, we describe algorithms that detect QRS-complex and decide whether it is normal or abnormal. The developed QRS detection algorithm is a simplified version of the conventional algorithm providing enough performance for the proposed application. The developed classification algorithm that detects abnormal from mostly normal beats is based on QRS width, R-R interval and QRS shape parameter using Karhunen-Loeve transformation. The simplified QRS detector correctly detected about 99% of all beats in the MTT/BIH ECG database. The classification algorithm correctly classified about 96% of beats as normal or abnormal. The QRS detection and classification algorithm described in this paper could be used in home health management system.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.9-18
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• 2011

In this paper, we propose a method which recognizes human activity using model-based gaze direction estimation in an indoor environment. The method consists of two steps. First, we detect a head region and estimate its gaze direction as prior information in the human activity recognition. We use color and shape information for the detection of head region and use Bayesian Network model representing relationships between a head and a face for the estimation of gaze direction. Second, we recognize event and scenario describing the human activity. We use change of human state for the event recognition and use a rule-based method with combination of events and some constraints. We define 4 types of scenarios related to the gaze direction. We show performance of the gaze direction estimation and human activity recognition with results of experiments.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.570-579
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• 2005

Facial expression recognition technology that has potentialities for applying various fields is appling on the man-machine interface development, human identification test, and restoration of facial expression by virtual model etc. Using sequential facial images, this study proposes a simpler method for detecting human facial expressions such as happiness, anger, surprise, and sadness. Moreover the proposed method can detect the facial expressions in the conditions of the sequential facial images which is not rigid motion. We identify the determinant face and elements of facial expressions and then estimates the feature regions of the elements by using information about color, size, and position. In the next step, the direction patterns of feature regions of each element are determined by using optical flows estimated gradient methods. Using the direction model proposed by this study, we match each direction patterns. The method identifies a facial expression based on the least minimum score of combination values between direction model and pattern matching for presenting each facial expression. In the experiments, this study verifies the validity of the Proposed methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.191-198
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• 2013

This paper proposes detection of view reversal in a stereo video using depth map and motion vector information. We obtain a depth map by using a stereo matching and divide the input image into foreground and background. Next, we obtain a motion vector field by using a motion estimation. In general, an occluded region is in background when foreground goes toward the adjacent background or the background goes toward the adjacent foreground. But, we will face with the change of foreground and background because their depths also change when view reversal occurs. Therefore, we can detect the view reversal in stereo videos by using the observation that the foreground goes toward the adjacent background or the background goes toward the adjacent foreground. The experimental results show that the proposed algorithm achieves good detection rate when the background region is sufficiently occluded by the moving foreground.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.482-488
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• 2009

Mobile Ad-hoc Networks provide communication without a centralized infrastructure, which makes them suitable for communication in disaster areas or when quick deployment is needed. On the other hand, they are susceptible to malicious exploitation and have to face different challenges at different layers due to its open Ad-hoc network structure which lacks previous security measures. Denial of service (DoS) attack is one that interferes with the radio transmission channel causing a jamming attack. In this kind of attack, an attacker emits a signal that interrupts the energy of the packets causing many errors in the packet currently being transmitted. In harsh environments where there is constant traffic, a jamming attack causes serious problems; therefore measures to prevent these types of attacks are required. The objective of this paper is to carry out the simulation of the jamming attack on the nodes and determine the DoS attacks in OPNET so as to obtain better results. We have used effective anomaly detection system to detect the malicious behaviour of the jammer node and analyzed the results that deny channel access by jamming in the mobile Ad-hoc networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1120-1131
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• 2016

In this paper, we propose a smoker recognition algorithm, detecting smokers in a video sequence in order to prevent fire accidents. We use description-based method in hierarchical approaches to recognize smoker's activity, the algorithm consists of background subtraction, object detection, event search, event judgement. Background subtraction generates slow-motion and fast-motion foreground image from input image using Gaussian mixture model with two different learning-rate. Then, it extracts object locations in the slow-motion image using chain-rule based contour detection. For each object, face is detected by using Haar-like feature and smoke is detected by reflecting frequency and direction of smoke in fast-motion foreground. Hand movements are detected by motion estimation. The algorithm examines the features in a certain interval and infers that whether the object is a smoker. It robustly can detect a smoker among different objects while achieving real-time performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.53-60
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• 2009

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking; and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.603-607
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• 2004

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1089-1098
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• 2009

Recently, many researches of making more comfortable input device based on gaze detection technology have been performed in human computer interface. Previous researches were performed on the computer environment with a large sized monitor. With recent increase of using mobile device, the necessities of interfacing by gaze detection on mobile environment were also increased. In this paper, we research about the gaze detection method by using UMPC (Ultra-Mobile PC) and an embedded camera of UMPC based on face and facial feature detection by AAM (Active Appearance Model). This paper has following three originalities. First, different from previous research, we propose a method for tracking user's gaze position in mobile device which has a small sized screen. Second, in order to detect facial feature points, we use AAM. Third, gaze detection accuracy is not degraded according to Z distance based on the normalization of input features by using the features which are obtained in an initial user calibration stage. Experimental results showed that gaze detection error was 1.77 degrees and it was reduced by mouse dragging based on the additional facial movement.

• Journal of Genetic Medicine
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• v.15 no.2
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• pp.102-106
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• 2018

Aggrecan is a proteoglycan in the extracellular matrix of growth plate and cartilaginous tissues. Aggrecanopathy has been reported as a genetic cause not only for severe skeletal dysplasia but also for autosomal dominant short stature with normal to advanced bone age. We report a novel heterozygous mutation of ACAN in a Korean family with proportionate short stature identified through targeted exome sequencing. We present a girl of 4 years and 9 months with a family history of short stature over three generations. The paternal grandmother is 143 cm tall (-3.8 as a Korean standard deviation score [SDS]), the father 155 cm (-3.4 SDS), and the index case 96.2 cm (-2.9 SDS). Evaluation for short stature showed normal growth hormone (GH) peaks in the GH provocation test and a mild delayed bone age for chronological age. This subject had clinical characteristics including a triangular face, flat nasal bridge, prognathia, blue sclerae, and brittle teeth. The targeted exome sequencing was applied to detect autosomal dominant growth palate disorder. The novel variant c.910G>A (p.Asp304Asn) in ACAN was identified and this variant was found in the subject's father using Sanger sequencing. This is the first case of Korean familial short stature due to ACAN mutation. ACAN should be considered for proportionate idiopathic short stature, especially in cases of familial short stature.