• Journal of Korea Society of Industrial Information Systems
• /
• 제16권4호
• /
• pp.9-18
• /
• 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 Digital Contents Society
• /
• 제19권7호
• /
• pp.1397-1403
• /
• 2018

Today, modern people perceive skin care as part of their physical health care, and acne is a common skin disease problem that is found on the face. In this paper, an effective acne detection algorithm using CIE $L^*a^*b^*$ color space has been proposed. It is red when the pixel value of the component image $a^*$ is a positive number, so it is suitable for detecting acne in skin image. First, the skin image based on the RGB color space is subjected to light compensation through color balancing, and converted into a CIE $L^*a^*b^*$ color space. The extracted component image $a^*$ was normalized, and then the skin and acne area were estimated with the threshold values. Experimental results show that the proposed method detects acne more effectively than the conventional method based on brightness information, and the proposed method is robust against the reflected light source.

• Journal of the Korea Society of Computer and Information
• /
• 제10권4호
• /
• pp.47-56
• /
• 2005

With the development of wearable(ubiquitous) computers, those traditional interfaces between human and computers gradually become uncomfortable to use, which directly leads to a requirement for new one. In this paper, we study on a new interface in which computers try to recognize the gesture of human through a digital camera. Because the method of recognizing hand gesture through camera is affected by the surrounding environment such as lighting and so on, the detector should be a little sensitive. Recently, Viola's detector shows a favorable result in face detection. where Adaboost learning algorithm is used with the Haar features from the integral image. We apply this method to hand area detection and carry out comparative experiments with the classic method using skin color. Experimental results show Viola's detector is more robust than the detection method using skin color in the environment that degradation may occur by surroundings like effect of lighting.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• 제45권3호
• /
• pp.55-63
• /
• 2008

This paper presents a panorama background generation and object tracking technique using a Pan-Tilt-Zoom camera. The proposed method estimates local motion vectors rapidly using phase correlation matching at the prespecified multiple local regions, and it makes minimized estimation error by vector quantization. We obtain the required image patches, by estimating the overlapped region using local motion vectors, we can then project the images to cylinder and realign the images to make the panoramic image. The object tracking is performed by extracting object's motion and by separating foreground from input image using background subtraction. The proposed PTZ-based object tracking method can efficiently generated a stable panorama background, which covers up to 360 degree FOV The proposed algorithm is designed for real-time implementation and it can be applied to many commercial applications such as object shape detection and face recognition in various surveillance video systems.

• KIISE Transactions on Computing Practices
• /
• 제21권8호
• /
• pp.549-554
• /
• 2015

As intuitive hardware interfaces continue to be developed, it has become more important to recognize the posture of the user. An efficient alternative to adding expensive sensors is to implement computer vision systems. This paper proposes a method to recognize a user's postured in a live broadcast bi-directional participatory TV program. The proposed method first estimates the position of the user's hands by generation a facial color map for the user and a motion map. The posture is then recognized by computing the relative position of the face and the hands. This method exhibited 90% accuracy in an experiment to recognize three defined postures during the live broadcast bi-directional participatory TV program, even when the input images contained a complex background.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• 제23권12호
• /
• pp.1492-1499
• /
• 2019

This paper propose how to track the position of the observer to control the viewing zone using an adaptive parallax barrier. The pose is estimated using a Constrained Local Model based on the shape model and Landmark for robust eye-distance measurement in the face pose. Camera's correlation converts distance and horizontal location to centimeter. The pixel pitch of the adaptive parallax barrier is adjusted according to the position of the observer's eyes, and the barrier is moved to adjust the viewing area. This paper propose a method for tracking the observer in the range of 60cm to 490cm, and measure the error, measurable range, and fps according to the resolution of the camera image. As a result, the observer can be measured within the absolute error range of 3.1642cm on average, and it was able to measure about 278cm at 320×240, about 488cm at 640×480, and about 493cm at 1280×960 depending on the resolution of the image.

• Proceedings of the IEEK Conference
• /
• 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
• /
• pp.21-24
• /
• 2001

In this paper, we present a fast face detection algorithm by estimating the eye region using neural network. To implement a real time face detection system, it is necessary to reduce search space. We limit the search space just to a few pairs of eye candidates. For the selection of them, we first isolate possible eye regions in the fast and robust way by modified histogram equalization. The eye candidates are paired to form an eye pair and each of the eye pair is estimated how close it is to a true eye pair in two aspects : One is how similar the two eye candidates are in shape and the other is how close each of them is to a true eye image A multi-layer perceptron neural network is used to find the eye candidate region's closeness to the true eye image. Just a few best candidates are then verified by eigenfaces. The experimental results show that this approach is fast and reliable. We achieved 94% detection rate with average 0.1 sec Processing time in Pentium III PC in the experiment on 424 gray scale images from MIT, Yale, and Yonsei databases.

• Journal of the Korea Computer Industry Society
• /
• 제7권5호
• /
• pp.545-554
• /
• 2006

RFID could be applied in the various fields such as distribution beside, circulation, traffic and environment on information communication outside. So this can speak as point of ubiquitous computing's next generation technology. However, it is discussed problem of RFID security recently, so we must prepare thoroughly about RFID security for secure information. In this paper, we proposed a method which could protect private information and ensure RFID's identification effectively storing face feature information on RFID tag. Our method which is improved linear discriminant analysis has reduced dimension of feature information which has large size of data. Therefore, we can sore face feature information in small memory field of RFID tag. Our propose d algorithm has shown 92% recognition rate in experimental results and can be applied to entrance control management system, digital identification card and others.

• Journal of the Semiconductor & Display Technology
• /
• 제4권1호
• /
• pp.61-64
• /
• 2005

This study presents a new algorithm to detect the facial feature in a color image entered from the mobile device with complex backgrounds and undefined distance between camera's location and the face. Since skin color model with Hough transformation spent approximately 90$\%$ of running time to extract the fitting ellipse for detection of the facial feature, we have changed the approach to the simple geometric vector operation, called a TS(Triangle-Square) transformation. As the experimental results, this gives benefit of reduced run time. We have similar ratio of face detection to other methods with fast speed enough to be used on real-time identification system in mobile environments.

• Journal of the korean academy of Pediatric Dentistry
• /
• 제31권3호
• /
• pp.481-485
• /
• 2004

Rabson-Mendenhall syndrome(RMS) is first characterized in 1955 by Rabson and Mendenhall. RMS is a rare autosomal recessive variant with insulin resistance. This is due to insulin receptor mutations or other target-cell defects in insulin action. General findings include acanthosis nigricans, hypertrichosis, onychauxis, growth retardation, precocious puberty, genital enlargement, protuberant abdomen and xerotic skin. Characteristic oral and maxillofacial findings include dental dysplasia, coarse facial skin, prognathic jaw and fissured tongue. In this case report, dental characteristics of a 4-year old boy with Rabson-Mendenhall syndrome are described.