• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.41-47
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• 2012

MANET has vulnerable structure on security owing to structural characteristics as follows. MANET consisted of moving nodes is that every nodes have to perform function of router. Every node has to provide reliable routing service in cooperation each other. These properties are caused by expose to various attacks. But, it is difficult that position of environment intrusion detection system is established, information is collected, and particularly attack is detected because of moving of nodes in MANET environment. It is not easy that important profile is constructed also. In this paper, conformal predictor - support vector machine(CP-SVM) based intrusion detection technique was proposed in order to do more accurate and efficient intrusion detection. In this study, IDS-agents calculate p value from collected packet and transmit to cluster head, and then other all cluster head have same value and detect abnormal behavior using the value. Cluster form of hierarchical structure was used to reduce consumption of nodes also. Effectiveness of proposed method was confirmed through experiment.

• Smart Media Journal
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• v.7 no.4
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• pp.61-69
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• 2018

Multi-tracking of general objects and specific faces is an important topic in the field of computer vision applicable to many branches of industry such as biometrics, security, etc. The rapid development of deep neural networks has resulted in a dramatic improvement in face recognition and object detection problems, which helps improve the multiple-face tracking techniques exploiting the tracking-by-detection method. Our proposed method uses face detection trained with a head dataset to resolve the face deformation problem in the tracking process. Further, we use robust face features extracted from the deep face recognition network to match the tracklets with tracking faces using Hungarian matching method. We achieved promising results regarding the usage of deep face features and head detection in a face tracking benchmark.

• ETRI Journal
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• v.34 no.4
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• pp.542-552
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• 2012

In this paper, a gaze estimation method is proposed for use with a large-sized display at a distance. Our research has the following four novelties: this is the first study on gaze-tracking for large-sized displays and large Z (viewing) distances; our gaze-tracking accuracy is not affected by head movements since the proposed method tracks the head by using a near infrared camera and an infrared light-emitting diode; the threshold for local binarization of the pupil area is adaptively determined by using a p-tile method based on circular edge detection irrespective of the eyelid or eyelash shadows; and accurate gaze position is calculated by using two support vector regressions without complicated calibrations for the camera, display, and user's eyes, in which the gaze positions and head movements are used as feature values. The root mean square error of gaze detection is calculated as $0.79^{\circ}$ for a 30-inch screen.

• 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.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1993.05a
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• pp.87-87
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• 1993

Polymerase chain reaction is widely used as a powerful tool in modern molecular biology. As there is agreement that the HPV is an important factor in the head and neck cancers, the detection of HPV DNA sequence in the head and neck cancer tissue has been tried in several ways. We used the PCR to detect the E1 open reading frames of the HPV in paraffin-embedded tissue of the patients with the head neck cancers. Eleven of the fifty-four tested samples (30%) showed positive result. We have analysed the clinical courses and characteristics related with Human Papillomavirus in those patients.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.601-602
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• 2011

In this paper, we propose head/rear lamp detection algorithm for stopped and wrong way vehicle recognition. It is shown that our algorithm detected vehicles based on the experimental analysis about the color information of vehicle's lamps. The simulation results show the detection rate about stopped and wrong way vehicles is achieved over 94% and 96% in the tunnel HD(High Definition) video image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.49-64
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• 2008

Recently, many researches about making more comfortable input device based on gaze detection technology have been done in human computer interface. However, the system cost becomes high due to the complicated hardware and there is difficulty to use the gaze detection system due to the complicated user calibration procedure. In this paper, we propose a new gaze detection method based on the 2D analysis and a simple user calibration. Our method used a small USB (Universal Serial Bus) camera attached on a HMD (Head-Mounted Display), hot-mirror and IR (Infra-Red) light illuminator. Because the HMD is moved according to user's facial movement, we can implement the gaze detection system of which performance is not affected by facial movement. In addition, we apply our gaze detection system to 3D first person shooting game. From that, the gaze direction of game character is controlled by our gaze detection method and it can target the enemy character and shoot, which can increase the immersion and interest of game. Experimental results showed that the game and gaze detection system could be operated at real-time speed in one desktop computer and we could obtain the gaze detection accuracy of 0.88 degrees. In addition, we could know our gaze detection technology could replace the conventional mouse in the 3D first person shooting game.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.38-44
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• 2018

In this paper, we propose Intelligent Driver Assistance System (I-DAS) for driver safety. The proposed system recognizes safety and danger status by analyzing blind spots that the driver cannot see because of a large angle of head movement from the front. Most studies use image pre-processing such as face detection for collecting information about the driver's head movement. This not only increases the computational complexity of the system, but also decreases the accuracy of the recognition because the image processing system dose not use the entire image of the driver's upper body while seated on the driver's seat and when the head moves at a large angle from the front. The proposed system uses a convolutional neural network to replace the face detection system and uses the entire image of the driver's upper body. Therefore, high accuracy can be maintained even when the driver performs head movement at a large angle from the frontal gaze position without image pre-processing. Experimental result shows that the proposed system can accurately recognize the dangerous conditions in the blind zone during operation and performs with 95% accuracy of recognition for five drivers.

• Structural Engineering and Mechanics
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• v.65 no.2
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• pp.129-139
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• 2018

Post-tensioning (PT) tendons are commonly used for the assembly of modularized concrete members, and tension is applied to the tendons during construction to facilitate the integrated behavior of the members. However, the tension in a PT tendon decreases over time due to steel corrosion and concrete creep, and consequently, the stress on the anchor head that secures the PT tendon also diminishes. This study proposes an automatic detection system to identify tension reduction in a PT tendon using pulsed-eddy-current (PEC) measurement. An eddy-current sensor is installed on the surface of the steel anchor head. The sensor creates a pulsed excitation to the driving coil and measures the resulting PEC response using the pick-up coil. The basic premise is that the tension reduction of a PT tendon results in stress reduction on the anchor head surface and a change in the PEC intensity measured by the pick-up coil. Thus, PEC measurement is used to detect the reduction of the anchor head stress and consequently the reduction of the PT tendon force below a certain threshold value. The advantages of the proposed PEC-based tension-reduction-detection (PTRD) system are (1) a low-cost (< $ 30), low-power (< 2 Watts) sensor, (2) a short inspection time (< 10 seconds), (3) high reliability and (4) the potential for embedded sensing. A 3.3 m long full-scale monostrand PT tendon was used to evaluate the performance of the proposed PTRD system. The PT tendon was tensioned to 180 kN using a custom universal tensile machine, and the tension was decreased to 0 kN at 20 kN intervals. At each tension, the PEC responses were measured, and tension reduction was successfully detected.