• Title/Summary/Keyword: local information

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Local Map Building Using the information of a Range Finder (영역 검출기 정보를 이용한 지역 지도 작성)

  • Ko, Nak-Yong;Choi, Woong;Choi, Jung-Sang
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.9 no.1
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    • pp.102-110
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    • 2000
  • This paper presents an algorithm of local map building for autonomous robot navigation using LASER range finder information. We develop a model of sensor output for a LASER range finder, and obtain an output data of the LASER range finder for a given environment. From the output data, a local map is obtained through the following procedures: (1) filtering of output data to remove noisy and unnecessary data, (2) comparison of filtered data with the original data to restore useful data, (3) thickening of the map obtained from the restored data, and (4) skeletonizing of the thickened map to get a final local map. Through some simulation studies, a map is obtained from the LASER range finder information for a given indoor environment, and is compared with the environment.

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IMAGE SEGMENTATION BASED ON THE STATISTICAL VARIATIONAL FORMULATION USING THE LOCAL REGION INFORMATION

  • Park, Sung Ha;Lee, Chang-Ock;Hahn, Jooyoung
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.18 no.2
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    • pp.129-142
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    • 2014
  • We propose a variational segmentation model based on statistical information of intensities in an image. The model consists of both a local region-based energy and a global region-based energy in order to handle misclassification which happens in a typical statistical variational model with an assumption that an image is a mixture of two Gaussian distributions. We find local ambiguous regions where misclassification might happen due to a small difference between two Gaussian distributions. Based on statistical information restricted to the local ambiguous regions, we design a local region-based energy in order to reduce the misclassification. We suggest an algorithm to avoid the difficulty of the Euler-Lagrange equations of the proposed variational model.

Scence Change Adaptive Bit Rate Control Using Local Variance (국부 분산을 이용한 장면 전환 적응 비트율 제어)

  • 이호영;김기석;박영식;송근원;남재열;하영호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.4
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    • pp.675-684
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    • 1997
  • The bit rate control algorithm which is capable of handing scene change is proposed. In MPEG-2 TM5, block variance is used to measure block activity. But block variance is not consistent with human visual system and does not differenciate the distribution of pixel values within the block. In target bit allocation process of TM5, global complexity, obtained by results of previous coded pictures, is used. Since I pictures are spaced relatively far apart, their complexity estimate is not very accurate. In the proposed algorithm local variance is used to measure block activity and detect scene change. Local variance, using deviation from the mean of neighboring pixels, well represents the distribution of pixel values within the block. If scene change is detected, the local variance information is used for target bit allocation process. Allocating target bits for I picture, the average local variance difference between previous and current I picture is considered. The experimental results show that the proposed algorithm can detect scene change very precisely and gives better picture quality and higher PSNR values than MPEG-2 TM5.

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Texture Classification Using Local Neighbor Differences (지역 근처 차이를 이용한 텍스쳐 분류에 관한 연구)

  • Saipullah, Khairul Muzzammil;Peng, Shao-Hu;Park, Min-Wook;Kim, Deok-Hwan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2010.04a
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    • pp.377-380
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    • 2010
  • This paper proposes texture descriptor for texture classification called Local Neighbor Differences (LND). LND is a high discriminating texture descriptor and also robust to illumination changes. The proposed descriptor utilizes the sign of differences between surrounding pixels in a local neighborhood. The differences of those pixels are thresholded to form an 8-bit binary codeword. The decimal values of these 8-bit code words are computed and they are called LND values. A histogram of the resulting LND values is created and used as feature to describe the texture information of an image. Experimental results, with respect to texture classification accuracies using OUTEX_TC_00001 test suite has been performed. The results show that LND outperforms LBP method, with average classification accuracies of 92.3% whereas that of local binary patterns (LBP) is 90.7%.

The global standard realizing process of the Automobile Assembly Facility

  • Nashimoto, Tomoo
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.24-25
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    • 2015
  • To realize the global standard of the assembly facility, one of key point is an influence of local characteristic. The global standardized information could be a useful input, especially at the beginning stage of the project. The content should be carefully checked against local requirements, in order to develop an Assembly Facility design to meet local regulations & characteristics. The level of input information required in each step is different depend on regions & countries. At an execution stage of the project, the global standard input needs to be updated as customized final input for the construction. There will be many issues to be clarified and coordinated so that the Assembly facilities meet the final requirements for the production technology. As a result, it is important to understand the timing to use the global standard information and the contents what is needed to adapt to the local characteristics. And close collaboration between production technology team and facility team is always required.

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The Contribution Strategy of Public Library to Local Cultural Development in Korea (공공도서관의 지역문화발전 기여전략 연구)

  • Yoon, Hee-Yoon
    • Journal of Korean Library and Information Science Society
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    • v.46 no.4
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    • pp.1-20
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    • 2015
  • The goal of this study is to propose the contribution strategies of public library as cultural infrastructure to local cultural development in Korea. For this goal, researcher evaluated how public libraries contribute to the local cultural development in terms of interdependence of public library and local culture. Then, the researcher divided into the local culture to knowledge culture, reading culture, learning culture, living culture, and leisure culture, and suggested six contribution strategies(improving core competencies including the collection development and user service, strengthening education and support for digital information literacy, reading promotion and base expansion for everyday life, optimization of lifelong learning & culture program services, increasing openness and friendliness of the facilities and space, expansion of cooperation with relevant agencies) of public library for their development and promotion.

Human Action Recognition Bases on Local Action Attributes

  • Zhang, Jing;Lin, Hong;Nie, Weizhi;Chaisorn, Lekha;Wong, Yongkang;Kankanhalli, Mohan S
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.1264-1274
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    • 2015
  • Human action recognition received many interest in the computer vision community. Most of the existing methods focus on either construct robust descriptor from the temporal domain, or computational method to exploit the discriminative power of the descriptor. In this paper we explore the idea of using local action attributes to form an action descriptor, where an action is no longer characterized with the motion changes in the temporal domain but the local semantic description of the action. We propose an novel framework where introduces local action attributes to represent an action for the final human action categorization. The local action attributes are defined for each body part which are independent from the global action. The resulting attribute descriptor is used to jointly model human action to achieve robust performance. In addition, we conduct some study on the impact of using body local and global low-level feature for the aforementioned attributes. Experiments on the KTH dataset and the MV-TJU dataset show that our local action attribute based descriptor improve action recognition performance.

Using Non-Local Features to Improve Named Entity Recognition Recall

  • Mao, Xinnian;Xu, Wei;Dong, Yuan;He, Saike;Wang, Haila
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2007.11a
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    • pp.303-310
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    • 2007
  • Named Entity Recognition (NER) is always limited by its lower recall resulting from the asymmetric data distribution where the NONE class dominates the entity classes. This paper presents an approach that exploits non-local information to improve the NER recall. Several kinds of non-local features encoding entity token occurrence, entity boundary and entity class are explored under Conditional Random Fields (CRFs) framework. Experiments on SIGHAN 2006 MSRA (CityU) corpus indicate that non-local features can effectively enhance the recall of the state-of-the-art NER systems. Incorporating the non-local features into the NER systems using local features alone, our best system achieves a 23.56% (25.26%) relative error reduction on the recall and 17.10% (11.36%) relative error reduction on the F1 score; the improved F1 score 89.38% (90.09%) is significantly superior to the best NER system with F1 of 86.51% (89.03%) participated in the closed track.

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Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system

  • Oh, Seung-Hoon;Maeng, Ju-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.6
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    • pp.29-35
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    • 2021
  • In this paper, we propose a method that combines KNN(K-Nearest Neighbor), Local Map Classification and Bayes Filter as a way to increase the accuracy of location positioning. First, in this technique, Local Map Classification divides the actual map into several clusters, and then classifies the clusters by KNN. And posterior probability is calculated through the probability of each cluster acquired by Bayes Filter. With this posterior probability, the cluster where the robot is located is searched. For performance evaluation, the results of location positioning obtained by applying KNN, Local Map Classification, and Bayes Filter were analyzed. As a result of the analysis, it was confirmed that even if the RSSI signal changes, the location information is fixed to one cluster, and the accuracy of location positioning increases.

A Novel of Mobile Commerce and Information Notice System for Local Festival Content Activation based on Location Information (위치 정보기반의 지역 축제 콘텐츠 활성화를 위한 모바일 커머스 및 정보 알림 시스템에 관한 연구)

  • Jung, Se Hoon;Park, Sun Min;Sim, Chun Bo
    • Journal of Korea Multimedia Society
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    • v.18 no.6
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    • pp.780-791
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    • 2015
  • Recently, it is being held festival according to regional and seasonally cultural feature in nationwide. Especially, local festivals are being provided festival information services a variety of forms for tourists depending on development of information device. However, systems to provide notification information of local festivals are not persistent but mostly short term service. In this paper, we propose a mobile commerce and information notification system through festival information alerts and festival surrounding information using local based on service. In addition, we implement a festival information notification system that applies to beacon based on bluetooth in order to inform them on diverse festival. Finally, we take into account in terms of design of system using object-oriented design modeling to improve reusability of proposed system.