• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.234-243
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• 2006

The recent rapid development of HCI and surveillance technologies has brought great interests in application systems to process faces. Much of research efforts in these systems has been primarily focused on such areas as face recognition, facial expression analysis and facial feature extraction. However, not many approaches have been reported toward face direction detection. This paper proposes a method to detect the direction of a face using a facial feature called facial triangle, which is formed by two eyebrows and the lower lip. Specifically, based on the single monocular view of the face, the proposed method introduces very simple formulas to estimate the horizontal or vertical rotation angle of the face. The horizontal rotation angle can be calculated by using a ratio between the areas of left and right facial triangles, while the vertical angle can be obtained from a ratio between the base and height of facial triangle. Experimental results showed that our method makes it possible to obtain the horizontal angle within an error tolerance of ${\pm}1.68^{\circ}$, and that it performs better as the magnitude of the vertical rotation angle increases.

• The Journal of the Korean dental association
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• v.32 no.8 s.303
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• pp.581-587
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• 1994

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.2
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• pp.321-327
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• 1999

In this progressed super-impose individual recognition system, the photograph of a skull was caught by CCD-camcoder with the MPEG, and an ante-mortem photograph was read by scanner. These two images were processed and superimposed using horizontal angle and vertical angle of face using the forensic dental medicine theory. The enhancement of super-impose individual recognition by anatomical references was performed on the two superimposed images of the same angle using the facial triangle and histogram analysis scheme.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.15-20
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• 2018

There are a lot of problems in the face detection area. One of them is detecting faces by facial features and reducing number of the false negatives and positions. This paper is directed to solve this problem by the proposed triangle method. Also, this paper explans cascades, Haar-like features, AdaBoost, HOG. We propose a scheme using 12-net, 24-net, 48-net to scan images and improve efficiency. Using triangle method for frontal pose, B and B1 methods for other poses in neural networks are proposed.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.151-159
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• 2006

In this paper. we Present an estimation method of a face pose by using two camera images. First, it finds corresponding facial feature points of eyebrow, eye and lip from two images After that, it computes three dimensional location of the facial feature points by using the triangulation method of stereo vision techniques. Next. it makes a triangle by using the extracted facial feature points and computes the surface normal vector of the triangle. The surface normal of the triangle represents the direction of the face. We applied the computed face pose to display a 3D face model. The experimental results show that the proposed method extracts correct face pose.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.11
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• pp.1487-1499
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• 2007

In this study, photographs of 600 Korean females aged from 20 to 50years old were indirectly measured in Venus face 2D program. The measurements were analyzed by statistical methods. The purpose of this study was to differentiate the facial types of adult women for the beauty industry. As a result of factor analysis, 6 factors were selected the key factors of facial shape: head height(factor 1), head width(factor 2), side face width(factor 3), head width and circumference(factor 4), face length(factor 5), and side face width(factor 6). We categorized facial type into 5 groups with the previous 6 factor. 5 types were most common facial shapes: Oblong face(type 1), Square face(type 2), Oval face(type 3), Round face(type 4), Triangle face(type 5). The results of facial type analysis were showed that Round face(26.6%), Triangle face(25.3%), Oval face(22.3%), Square face(20.0%), Oblong face(5.7%).

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1187-1193
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• 2013

In this paper, we present realistic 3D head modeling and facial expression systems. For 3D head modeling, we perform generic model fitting to make individual head shape and texture mapping. To calculate the deformation function in the generic model fitting, we determine correspondence between individual heads and the generic model. Then, we reconstruct the feature points to 3D with simultaneously captured images from calibrated stereo camera. For texture mapping, we project the fitted generic model to image and map the texture in the predefined triangle mesh to generic model. To prevent extracting the wrong texture, we propose a simple method using a modified interpolation function. For generating 3D facial expression, we use the vector muscle based algorithm. For more realistic facial expression, we add the deformation of the skin according to the jaw rotation to basic vector muscle model and apply mass spring model. Finally, several 3D facial expression results are shown at the end of the paper.

• Journal of Korea Multimedia Society
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• v.3 no.1
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• pp.23-33
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• 2000

In this paper, we describe an algorithm which can extract human faces with natural pose from complex backgrounds. This method basically adopts the concept that facial region has the nearly same gray level for all pixels within appropriately scaled blocks. Based on the idea, we develop a hierarchial process that first, a block image data with pyramid structure of input image is generated, and some candidate regions for facial regions in the block image are Quickly determined, then finally the detailed facial features; organs are decided. To find the features easily, we introduce a local gray level transform which emphasizes dark and small regions, and estimate the geometrical triangle constraints among the facial features. The merit of our method is that we can be freed from the parameter assignment problem since the algorithm utilize a simple brightness computation, consequently robust systems not being depended on specific parameter values can be easily constructed.

• Journal of Korea Game Society
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• v.14 no.2
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• pp.55-66
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• 2014

Image warping is a technology to transform input images to be suitable for given conditions and has been recently utilized in changing face shape of characters in the field of movies or animation. Mesh warping which is one of warping methods that change shapes based on the features of face forms warping images by forming rectangular mesh groups around the eyes, nose, and mouth and matching them 1:1. This method has a problem in the resultant images are distorted in the segments of boundaries between meshes when there are errors in mesh control points or when meshes have been formed as many small area meshes. This study proposes a triangle based image interpolation technique to minimize the occurrence of errors in the process of forming natural warping images of face and process accurate results with a small amount of arithmetic operation and a short time. First, feature points that represent the face are found and these points are connected to form basic triangle meshes. The fact that the proposed method can reduce errors occurring in the process of warping while reducing the amount of arithmetic operation and time is shown through experiments.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.385-386
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• 2007

In this paper, we present a detection method of facial angle using facial features. First, it finds face image using haar-like feature. After that, it finds eyes and lip in need of compute of face rotation angle. Next, it makes a triangle by using the facial features and computes the inside angle. As a result of experiment on various face images, the proposed method improves the efficiency much better than the conventional methods below $40^{\circ}$.