• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.492-501
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• 2009

Information on movement of objects in videos can be used as an important part in categorizing and separating the contents of a scene. This paper is proposing a shape-based movement-matching algorithm to effectively find the movement of an object in video streams. Information on object movement is extracted from the object boundaries from the input video frames becoming expressed in continuous 2D shape information while individual 2D shape information is converted into a lD shape feature using the shape descriptor. Object movement in video can be found as simply as searching for a word in a text without a separate movement segmentation process using the sequence of the shape descriptor listed according to order. The performance comparison results with the MPEG-7 shape variation descriptor showed that the proposed method can effectively express the movement information of the object and can be applied to movement search and analysis applications.

• Korean Journal of Computational Design and Engineering
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• v.20 no.4
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• pp.321-327
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• 2015

In the protein database search, 3D structural shape comparison for protein screening plays a important role. Protein databases have big size and have been grown rapidly. Exhaustive search methods cannot provide a satisfactory performance. As protein is composed of a set of spheres, the similarity calculation of two set of spheres is very expensive. Thus, a reasonable filtering method could be an answer for the speedup of protein screening. In this paper, we suggest a speedup method for protein screening with atom number and bounding sphere. We also show some experimental results for the validity of our method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.22-31
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• 2004

This paper deals with the dynamic hand gesture recognition based on computer vision using neural networks. This paper proposes a global search method and a local search method to recognize the hand gesture. The global search recognizes a hand among the hand candidates through the entire image search, and the local search recognizes and tracks only the hand through the block search. Dynamic hand gesture recognition method is based on the skin-color and shape analysis with the invariant moment and direction information. Starting point and ending point of the dynamic hand gesture are obtained from hand shape. Experiments have been conducted for hand extraction, hand recognition and dynamic hand gesture recognition. Experimental results show the validity of the proposed method.

• Journal of Fashion Business
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• v.21 no.5
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• pp.78-90
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• 2017

This study investigates the effects of appearance management behaviors on job search efficacy among female college students. Based on previous studies on appearance management behaviors and job search efficacy, the questionnaire items were developed. For the study, we conducted a questionnaire survey among 312 students from women's university in Seoul. The statistical analyses were performed using SPSS 23. The results were as follows. First, three types of appearance management factors have been identified: 'fashion & hair,' 'skin care & plastic surgery,' and 'body shape'; the reliability and validity of these factors were proved. Second, the appearance management behavior of female college students found to have a partially significant effect on job search efficacy: fashion & hair factor had a positive effect on job search strength; fashion & hair factor and body shape factor had a positive effect on job search skills. While skin care & plastic surgery factor had a negative effect on job search strength and job search skill. Third, between academic years, there were differences in job search efficacy but not in appearance management behavior. By majors, there were differences among skin care & plastic surgery factor, body shape factor, and job search strength factor. These results suggest that to improve the job search efficacy, proper appearance management through fashion and hair, and body shape management is necessary. In addition, it suggests that it is important to improve the effectiveness of employment by establishing the appearance management strategy that matches the characteristics of each major.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.395-400
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• 2011

In this paper, we propose an study of the facial emotion recognition considering the dynamical variation of emotional state in facial image sequences. The proposed system consists of two main step: facial image based emotional feature extraction and emotional state classification/recognition. At first, we propose a method for extracting and analyzing the emotional feature region using a combination of Active Shape Model (ASM) and Facial Action Units (FAUs). And then, it is proposed that emotional state classification and recognition method based on Hidden Markov Model (HMM) type of dynamic Bayesian network. Also, we adopt a Harmony Search (HS) algorithm based heuristic optimization procedure in a parameter learning of HMM in order to classify the emotional state more accurately. By using all these methods, we construct the emotion recognition system based on variations of the dynamic facial image sequence and make an attempt at improvement of the recognition performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.41-50
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• 2004

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6A
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• pp.369-378
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• 2012

In this study, direct-search based optimization methods are applied for blade shape optimization of wind turbines and the optimization performances of several methods including conventional genetic algorithm, micro genetic algorithm and pattern search method are compared to propose a more efficient method. For this purpose, the currently available version of HARP_Opt (Horizontal Axis Rotor Performance Optimizer) code is enhanced to rationally evaluate the annual energy production value according to control strategies and to optimize the blade shape using pattern search method as well as genetic algorithm. The enhanced HARP_Opt code is applied to obtain the optimal turbine blade shape for 1MW class wind turbines. The results from pattern search method are compared with the results from conventional genetic algorithm and also micro genetic algorithm and it is found that the pattern search method has a better performance in achieving higher annual energy production and consistent optimal shapes and the micro genetic algorithm is better for reducing the calculation time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.55-65
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• 2006

Most of fast block motion estimation algorithms reported so far in literatures aim to reduce the computation in terms of the number of search points, thus do not fit well with multimedia processors due to their irregular data flow. For multimedia processors, proper reuse of data is more important than reducing number of absolute difference operations because the execution cycle performance strongly depends on the number of off-chip memory access. Therefore, in this paper, we propose a Hexagon-shape line search (HEXSLS) algorithm using line search pattern which can increase data reuse from on-chip local buffer, and check sub-sampling points in line search pattern to reduce unnecessary SAD operation. Our experimental results show that the prediction error (MAE) performance of the proposed HEXSLS is similar to that of the full search block matching algorithm (FSBMA), while compared with the hexagon-based search (HEXBS), the HEXSLS outperforms. Also the proposed HEXSLS requires much lesser off-chip memory access than the conventional fast motion estimation algorithm such as the hexagon-based search (HEXBS) and the predictive line search (PLS). As a result, the proposed HEXSLS algorithm requires smaller number of execution cycles on media processor.

• Korean Journal of Computational Design and Engineering
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• v.14 no.6
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• pp.404-414
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• 2009

In the computational molecular analysis, 3D structural comparison for protein searching plays a very important role. As protein databases have been grown rapidly in size, exhaustive search methods cannot provide satisfactory performance. Because exhaustive search methods try to handle the structure of protein by using sphere set which is converted from atoms set, the similarity calculation about two sphere sets is very expensive. Instead, the filter-and-refine paradigm offers an efficient alternative to database search without compromising the accuracy of the answers. In recent, a very fast algorithm based on the inter-atomic distance has been suggested by Ballester and Richard. Since they adopted the moments of distribution with inter-atomic distance between atoms which are rotational invariant, they can eliminate the structure alignment and orientation fix process and perform the searching faster than previous methods. In this paper, we propose a new 3D shape descriptor. It has properties of the general shape distribution and useful property in screening the molecular database. We show some experimental results for the validity of our method.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.498-508
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• 2005

A shape data is used one oi most important feature for image retrieval as data to reflect meaning of image. Especially, structural feature of shape is widely studied because it represents primitive properties of shape and relation information between basic units well. However, most structural features of shape have the problem that it is not able to guarantee an efficient search time because the features are expressed as graph or tree. In order to solve this problem, we generate curvature-based morphological graph, End design key to cluster shapes from this graph. Proposed this graph have contour features and morphological features of a shape. Shape retrieval is accomplished by stages. We reduce a search space through clustering, and determine total similarity value through pattern matching of external curvature. Various experiments show that our approach reduces computational complexity and retrieval cost.