• Title/Summary/Keyword: 지역화된 템플릿

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Mobile Gesture Recognition using Dynamic Time Warping with Localized Template (지역화된 템플릿기반 동적 시간정합을 이용한 모바일 제스처인식)

  • Choe, Bong-Whan;Min, Jun-Ki;Jo, Seong-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.4
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    • pp.482-486
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    • 2010
  • Recently, gesture recognition methods based on dynamic time warping (DTW) have been actively investigated as more mobile devices have equipped the accelerometer. DTW has no additional training step since it uses given samples as the matching templates. However, it is difficult to apply the DTW on mobile environments because of its computational complexity of matching step where the input pattern has to be compared with every templates. In order to address the problem, this paper proposes a gesture recognition method based on DTW that uses localized subset of templates. Here, the k-means clustering algorithm is used to divide each class into subclasses in which the most centered sample in each subclass is employed as the localized template. It increases the recognition speed by reducing the number of matches while it minimizes the errors by preserving the diversities of the training patterns. Experimental results showed that the proposed method was about five times faster than the DTW with all training samples, and more stable than the randomly selected templates.

Multiple Classifier Fusion Method based on k-Nearest Templates (k-최근접 템플릿기반 다중 분류기 결합방법)

  • Min, Jun-Ki;Cho, Sung-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.4
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    • pp.451-455
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    • 2008
  • In this paper, the k-nearest templates method is proposed to combine multiple classifiers effectively. First, the method decomposes training samples of each class into several subclasses based on the outputs of classifiers to represent a class as multiple models, and estimates a localized template by averaging the outputs for each subclass. The distances between a test sample and templates are then calculated. Lastly, the test sample is assigned to the class that is most frequently represented among the k most similar templates. In this paper, C-means clustering algorithm is used as the decomposition method, and k is automatically chosen according to the intra-class compactness and inter-class separation of a given data set. Since the proposed method uses multiple models per class and refers to k models rather than matches with the most similar one, it could obtain stable and high accuracy. In this paper, experiments on UCI and ELENA database showed that the proposed method performed better than conventional fusion methods.

Pulmonary Nodule Registration using Template Matching in Serial CT Scans (연속 CT 영상에서 템플릿 매칭을 이용한 폐결절 정합)

  • Jo, Hyun-Hee;Hong, He-Len
    • Journal of KIISE:Software and Applications
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    • v.36 no.8
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    • pp.623-632
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    • 2009
  • In this paper, we propose a pulmonary nodule registration for the tracking of lung nodules in sequential CT scans. Our method consists of following five steps. First, a translational mismatch is corrected by aligning the center of optimal bounding volumes including each segmented lung. Second, coronal maximum intensity projection(MIP) images including a rib structure which has the highest intensity region in baseline and follow-up CT series are generated. Third, rigid transformations are optimized by normalized average density differences between coronal MIP images. Forth, corresponding nodule candidates are defined by Euclidean distance measure after rigid registration. Finally, template matching is performed between the nodule template in baseline CT image and the search volume in follow-up CT image for the nodule matching. To evaluate the result of our method, we performed the visual inspection, accuracy and processing time. The experimental results show that nodules in serial CT scans can be rapidly and correctly registered by coronal MIP-based rigid registration and local template matching.

A Study on Limesurvey in the Form of Open Source Online Survey System for Curriculum Organizing (학교 교육과정 편성을 위한 오픈 소스 온라인 설문조사 시스템 Limesurvey 활용 방안)

  • Han, Ki-Sun;Chun, Seok-Ju
    • 한국정보교육학회:학술대회논문집
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    • 2011.01a
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    • pp.91-101
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    • 2011
  • The purpose of this paper is to quickly identify school parents, teachers, students, community needs and opinions for curriculum organizing and the implementation of an online survey system for operating educational activities. Online survey system should be implemented based on Limesurvey to reduce costs and administrative costs. Limesurvery is available without the development of the separate program and offers the form of web-based template system, complete design, layout. Also, Limesurvey offers basic statistical analysis of survey data. Limesurvey can be executed by installing the program on a web hosting, typing database information. Limesurvey can be made a graph of the statistical results. Besides, Limesurvery can be stored in the form of HTML, Word, Excel, CSV Files and can be stured as basic datas for SPSS or PASW, R data, other statistical processing programs. If we could be operate Limesurvey in the form of open source-based survey program in elementary school, we could be reduced teacher's unnecessary work for statistics and overcame the problem of offline survey system.

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