• Journal of Biomedical Engineering Research
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• v.20 no.4
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• pp.419-425
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• 1999

In this paper, we present an algorithm of real time facial expression and gesture recognition for image sequence on the gray level. A mixture algorithm of a template matching and knowledge based geometrical consideration of a face were adapted to locate the face area in input image. And optical flow method applied on the area to recognize facial expressions. Also, we suggest hand area detection algorithm form a background image by analyzing entropy in an image. With modified hand area detection algorithm, it was possible to recognize hand gestures from it. As a results, the experiments showed that the suggested algorithm was good at recognizing one's facial expression and hand gesture by detecting a dominant motion area on images without getting any limits from the background image.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.50-63
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• 1995

In this paper, we propose a face recognition method using a neuro-fuzzy algorithm. In the preprocessing step, we extract the face part from the background image by tracking face boundaries. Then based on the a priori knowledge of human faces we extract the features such as widths of eyes and mouth, and distances from eye to nose and nose to mouth. In the recognition step. We use a neuro-fuzzy algorithm that employs a fuzzy membership function and modified error backpropagation algorithm. The former absorbs the variation of feature values and the latter shows good learning efficiency. Computer simulation results with 20 persons show that the proposed method gives higher recognition rate than the conventional ones.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.513-515
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• 2019

Techniques to recognize depth values using Kinect infrared projectors continue to evolve. Techniques to track human movements are being developed from the Marcris method to the Bimarris method. Capture of facial movement using Kinect has disadvantages that are not sophisticated. In addition, a method to control the gestures and movements on the face in real time requires much research. Therefore, this paper proposes a technique to create natural 3D image contents by studying technology to apply and control branding technology to extracted face recognition data using Kinect infrared method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.983-991
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• 2005

Human faces are commonly found in a video such as a drama and provide useful information for video content analysis. Therefore, face detection plays an important role in applications such as face recognition, and face image database management. In this paper, we propose a face detection algorithm based on pre-processing of scene change detection for indexing and cast searching in video. The proposed algorithm consists of three stages: scene change detection stage, face region detection stage, and eyes and mouth detection stage. Experimental results show that the proposed algorithm can detect faces successfully over a wide range of facial variations in scale, rotation, pose, and position, and the performance is improved by $24\%$with profile images comparing with conventional methods using color components.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2314-2318
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• 2010

For human-robot interaction, a robot should recognize the meaning of human behavior. In the case of static behavior such as face expression and sign language, the information contained in a single image is sufficient to deliver the meaning to the robot. In the case of dynamic behavior such as gestures, however, the information of sequential images is required. This paper proposes behavior classification by using fuzzy classifier to deliver the meaning of dynamic behavior to the robot. The proposed method extracts feature points from input images by a skeleton model, generates a vector space from a differential image of the extracted feature points, and uses this information as the learning data for fuzzy classifier. Finally, we show the effectiveness and the feasibility of the proposed method through experiments.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.34 no.4
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• pp.333-338
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• 2008

The evaluation for the visage volume was performed with human and dummy face using PRIMOS $body^{(R)}$. Three researchers measured the dummy face attached different volume of clay (6.6 mL, 13.2 mL, and 19.8 mL). It is identified that the high correlation between measured values and real volume ($R^2=0.99$). The percent (%) of relative standard deviation (RSD) of the data was shown below 10%. In Gage R&R analysis, the percent of contribution, the percent of study variation and distinct categories values were 0.78%, 8.85%, and 15% respectively. Therefore this method was regarded as the good standard condition in aspect of reproducibility and repetitiveness of data. The face volume variation was measured by PRIMOS $body^{(R)}$ on the face in participated 10 healthy Korean women volunteers. Subjects used the product once a day for two weeks as night sleeping pack. After application of the test products, the 3D image data of face were taken 1 and 2 weeks later. We found the face volume was significantly decreased after using products. In conclusion, this novel non-invasive technique was useful in measuring and visualizing alterations in face volume as a consequence of certain treatments. This system will provide a rapid and precise analysis of 3D topographical information for face.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.683-686
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• 1988

In the recognition of similar patterns like profile contours of human faces, feature measure plays important role. We extracted effective and general feature by B-spline approximation. The nodes and vertices of the approximated curve are normalized and used as features. Since the features have both local property of curvature extrema and global property by B-spline approximation, they are superior to those of curvature extrema of the profile contour. For the image data of six sets of 56 persons, some of which are ill-made, averaged accuracy rate of 97.6 % is obtained in recognizing combinational 333 test samples.

• Journal of Internet Computing and Services
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• v.7 no.3
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• pp.143-153
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• 2006

Facial feature detection is a basic technology in applications such as human computer interface, face recognition, face tracking and image database management. The speed of feature detection algorithm is one of the main issues for facial feature detection in real-time environment. Primary factors like a variation by lighting effect, location, rotation and complex background give an effect to decrease a detection ratio. A facial feature detection algorithm is proposed to improve the detection ratio and the detection speed. The proposed algorithm detects skin regions over the entire image improved by CLAHE, an algorithm for light compensation against varying lighting conditions. To extract facial feature points on detected skin regions, it uses appearance-based geometrical characteristics of a face. Since the method shows fast detection speed as well as efficient face-detection ratio, it can be applied in real-time application to face tracking and face recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.75-77
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• 2012

In this paper, We proposed that real-time pupil detection using local binarization at each region of eyes in image. In image obtained a single low-resolution web-camera, we detect a region of face using haar-like feature and then detect each region of eyes depending upon the rate of width and height of region of face respectively. In each region of eyes, we detect the pupil after local preprocessing and binarizing. This pupil detection can be variously used for HCI(Human-Computer Interface) systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.58-65
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• 2007

The method of 3D sound realization using 2 speakers provides two advantages: cheap and easy to build. In the case, crosstalk between 2 speakers has to be eliminated. To calculate and remove the effect of the crosstalk it is essential to find a rotation angle of human head correctly. In the paper, we suggest an algorithm to find the head angle of 2 channel system. We first detect a face area of the given image using Haar-like feature. After that, the eve detection using pre-processor and morphology method. Finally, we calculate the face rotation angle with the face andi the eye location. As a result of the experiment on various face images, the proposed method improves the efficiency much better than the conventional methods.