• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.228-246
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• 2011

A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1523-1526
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• 2002

In this paper, we propose a method fur measuring the dimensions of an arbitrary object using geometric relationship between a perspective projection image and a rectangular parallelepiped model. For recognizing the vertexes of the rectangular parallelepiped surrounding an arbitrary object, the method adopts a strategy that derives the equations for vertex recognition from the geometrical relationships for image formation between 2D image and the rectangular parallelepiped model. extracts from 2D image with vertical view features (or junctions) of minimum quadrangle circumscribing an arbitrary shape object, and then recognizes vertexes from the features with the equations. Finally, the dimensions of the object are calculated from these results of vertex recognition. By the experimental results, it is demonstrated that this method is very effective to recognize the vertexes of the arbitrary objects.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1775-1784
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• 1999

This paper proposes a method of removing unnecessary hidden nodes by a new cost function that evaluates the variance and the mean of hidden node outputs during training. The proposed cost function makes necessary hidden nodes be activated and unnecessary hidden nodes be constants. We can remove the constant hidden nodes without performance degradation. Using the CEDAR handwritten digit recognition, we have shown that the proposed method can remove the number of hidden nodes up to 37.2%, with higher recognition rate and shorter learning time.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.553-556
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• 1988

Recognition of IC chip pattern requires extraction of features, which have the information of vertex position and orientation. Edges are extracted and straightening algorithm is applied to the edges, so that lines are obtained. With these extracted data, the coordinate and orientation of all vertices are extracted and vertex-form matching is applied to the locally overlapped area of neighborhood frames to have global coordinate of IC chip.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.54-63
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• 2000

In this paper, we implemented cyber character that can do speech recognition, speech synthesis, Motion tracking and 3D animation. For speech recognition, we used Discrete-HMM algorithm with K-means 128 level vector quantization and MFCC feature vector. For speech synthesis, we used demi-syllables TD-PSOLA algorithm. For PC based Motion tracking, we present Fast Optical Flow like Method. And for animating 3D model, we used vertex interpolation with DirectSD retained mode. Finally, we implemented cyber character integrated above systems, which game calculating by the multiplication table with user and the cyber character always look at user using of Motion tracking system.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.1031-1032
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• 2006

A 3D model based face recognition system is generally inefficient in computation time because 3D face model consists of a large number of vertices. In this paper, we propose a novel 3D face representation algorithm to reduce the number of vertices and optimize its computation time.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1657-1662
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• 2017

Facial expression recognition systems using video devices have emerged as an important component of natural human-machine interfaces which contribute to various practical applications such as security systems, behavioral science and clinical practices. In this work, we present a new method to analyze, represent and recognize human facial expressions using a sequence of facial images. Under our proposed facial expression recognition framework, the overall procedure includes: accurate face detection to remove background and noise effects from the raw image sequences and align each image using vertex mask generation. Furthermore, these features are reduced by principal component analysis. Finally, these augmented features are trained and tested using Hidden Markov Model (HMM). The experimental evaluation demonstrated the proposed approach over two public datasets such as Cohn-Kanade and AT&T datasets of facial expression videos that achieved expression recognition results as 96.75% and 96.92%. Besides, the recognition results show the superiority of the proposed approach over the state of the art methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.2
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• pp.112-123
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• 1990

This paper presents a vertex-detecting of Hanguel patterns using nested contour shape. Inputed binary character patterns are transformed by distance transformation method and make a new file of transferred data by analysis of charactersitcs. A new vertex-detecting algorithm for recognizing Hanguel patterns using the two data files is proposed. This algorithm is able to reduce the projecting parts of Hanguel pattern, separate the connecting parts between different strokes, set the code number by transformed value of coorked features. It makes the output of results in order to apply the Hanguel recognition.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.206-216
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• 1986

In this paper, the moving distance and velocity of a single moving object are measured by sampling three frames in a two-dimensional line sequence image. The brightness of each frame is analyzed, and the bit data of their pixel are rearranged so that the difference image may be extracted. The parameters for recognition of the object are the gray level of the object, the number of vertex points and the distance between the vertex points. The moving distance obtained from the coordinate which is constructed by the bit processing of the data in the memory map of a microcomputer, and the moving velocity is obtained from the moving distance and the time interval between the first and second sampled frames.

• Korean Journal of Cognitive Science
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• v.1 no.2
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• pp.317-346
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• 1989

A congnitive shape decomposition method that agrees with human intuition is proposed for the conceptual recognition from sillouettes of objects. Descriptions specifying the structure of shape in terms of meaningful parts and relations have cognitive power and anthropomorphism. In general, man-made objects have a lot of collinear lines and regularity. For the cognitive decomposition of man-made objects, many heuristic rules based on the cognitive experimentation are applied on the context of collinerarity and regularity. The cognitive shape decomposition for the natural shape is carried out by analyzing the possible configuraitions of vertices and line segments for one concave vertex. A cost function for the configuation is designed by weighted sum of five criteria such as, the length of split line segment, the number of split line segments at concave vertex, the proximity of concave vertex, and the correspondence of vertices. These criteria are vased on the property of human perception such as proximtiy, symmetry, and simplicity. The most promising vertex os selected among three set of visible vertices by evaluating the cost function. A number of experiments conducted on the different types of shapes shows that the results correspond with human intuition.