• Title/Summary/Keyword: local representation

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공간 계층적 구조 기반 지역 기술자 활용 얼굴인식 기술 (Using Spatial Pyramid Based Local Descriptor for Face Recognition)

  • 김경태;최재영
    • 한국멀티미디어학회논문지
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    • 제20권5호
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    • pp.758-768
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    • 2017
  • In this paper, we present a novel method to extract face representation based on multi-resolution spatial pyramid. In our method, a face is subdivided into increasingly finer sub-regions (local regions) and represented at multiple levels of histogram representations. To cope with misaligned problem, patch-based local descriptor extraction has been also developed in a novel way. To preserve multiple levels of detail in local characteristics and also encode holistic spatial configuration, histograms from all levels of spatial pyramid are integrated by using dimensionality reduction and feature combination, leading to our spatial-pyramid face feature representation. We incorporate our proposed face features into general face recognition pipeline and achieve state-of-the-art results on challenging face recognition problems.

전통문화축제의 내실화방안 연구 (Developing Proposals for Korean Traditional Culture Festivals)

  • 정달영;박기종
    • 한국연극학
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    • 제48호
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    • pp.549-569
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    • 2012
  • Since 1995, the Local autonomy era has opened, local festivals have been increasing throughout the country. Traditional culture festivals are also increasing. Performing traditional culture festivals is effective for maintenance and transmission of traditional culture as well as creation and nurturing of local culture. They are also effective promoting local economy. Depending on realization level of character, place and costume based on historic research, traditional culture festivals are classified as the "Representation event" or the "Reenactment event". But there are two problems. The first is unexacting classification method for festival types made by Central government yearly. The second is unable to meet one of two goals which are protecting traditional culture and stimulating local economy throughout increasing tourists. The purpose of this study is to suggest improvement of classification method for festival types, and to offer two suggestions for ensure successful local festivals. First of all, I suggest advanced classification method for festival types. For more sophisticated collection process of national festival status, local government department should ensure purpose of festivals, and central government department should add 3 steps to existing process. For example professional committee for judgement of festival types should be founded for consulting of local and central government department. The second suggestion is reinforcement of historic research for the Representation of traditional culture event. The representation of traditional culture should focus on protection of tradition, and could be perfect by continuous historic research. The last suggestion is cooperation with local governments each other for the Reenactment of traditional culture event. The Reenactment of traditional culture should focus on promoting local economy by increasing tourists. So local governments who have similar traditional events should cooperate to get preventing loss of resource and overcome weakness of promoting.

필기의 구조적 표현에 의한 온라인 자동 서명 검증 기법 (A Technique for On-line Automatic Signature Verification based on a Structural Representation)

  • 김성훈;장문익;김재희
    • 한국정보처리학회논문지
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    • 제5권11호
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    • pp.2884-2896
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    • 1998
  • 온라인 서명검증을 위해서는 서명의 국부적인 형태가 중요한 판단 근거가 된다. 함수적 접근이나 매개변수적 접근과 같은 지금까지의 접근방법은 서명을 시간에 대한 함수로 나타내거나, 특징집합으로 표현함으로써, 서명의 국부적인 모양을 무시한 채로 서명검증에서 유용한 요소로 사용될 수 있는 국부적인 모양에서의 다양한 특징, 국부적인 모양의 변화, 형태의 복잡성 등을 사용하지 않았다. 이 논문에서는 서명을 구성 형태에 근거한 구조적인 표현 방법으로 나타내어 서명의 국부적인 모양의 분석과 중요한 부분에 대한 선택적인 사용이 가능한 새로운 접근방식의 서명 검증 기법을 제시하였다. 즉, 서명의 구조적 표현에 근거하여 국부적 가중치 적용방법과 진위판단을 위한 임계치의 개인별 차등화 방법을 고안하였고, 이에 대한 실험결과를 분석하였다.

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Three-Dimensional Shape Recognition and Classification Using Local Features of Model Views and Sparse Representation of Shape Descriptors

  • Kanaan, Hussein;Behrad, Alireza
    • Journal of Information Processing Systems
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    • 제16권2호
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    • pp.343-359
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    • 2020
  • In this paper, a new algorithm is proposed for three-dimensional (3D) shape recognition using local features of model views and its sparse representation. The algorithm starts with the normalization of 3D models and the extraction of 2D views from uniformly distributed viewpoints. Consequently, the 2D views are stacked over each other to from view cubes. The algorithm employs the descriptors of 3D local features in the view cubes after applying Gabor filters in various directions as the initial features for 3D shape recognition. In the training stage, we store some 3D local features to build the prototype dictionary of local features. To extract an intermediate feature vector, we measure the similarity between the local descriptors of a shape model and the local features of the prototype dictionary. We represent the intermediate feature vectors of 3D models in the sparse domain to obtain the final descriptors of the models. Finally, support vector machine classifiers are used to recognize the 3D models. Experimental results using the Princeton Shape Benchmark database showed the average recognition rate of 89.7% using 20 views. We compared the proposed approach with state-of-the-art approaches and the results showed the effectiveness of the proposed algorithm.

개선된 ICA 기저영상을 이용한 국부적 왜곡에 강인한 얼굴인식 (Face Recognition Robust to Local Distortion using Modified ICA Basis Images)

  • 김종선;이준호
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제33권5호
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    • pp.481-488
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    • 2006
  • 부공간 투영기술(subspace projection)을 이용한 얼굴인식기술의 성능은 이들 기저영상들(basis images)의 특징과 밀접한 관련이 있다. 특히 표정변화와 같은 국부적 왜곡이나 오클루전이 있는 경우의 인식성능은 기저영상들의 특징에 의해 영향을 받게 된다. 부공간 투영기반의 얼굴인식 방법이 오클루전이나 표정변화와 같은 국부적인 왜곡발생에 강인하려면 부분국부적 표현(part-based local representation)의 기저벡터를 갖는 것이 중요하다. 본 연구에서는 국부적 왜곡과 오클루전에 강인한 효과적인 부분국부적 표현방법을 제안한다. 제안한 방법을 LS-ICA(locally salient ICA) 방법이라고 명명하였다. LS-ICA방법은 ICA 구조I의 기저영상을 구하는 과정에서 공간적인 국부성(locality)의 제약조건을 부과함으로써 부분국부적 기저영상(part-based local basis images)을 얻는 방법이다. 결과적으로 공간적으로 현저한 특징만을 포함하는 기저영상을 사용하게 되며, 이는 "Recognition by Parts"의 방법론과 유사하다. LS-ICA방법과 LNMF(Localized Non-negative Matrix Factorization)와 LFA(Local Feature Analysis)와 같은 기존의 부분 표현방법(part-based representation)들에 대해 다양한 얼굴영상 데이타베이스를 사용하여 실험한 결과, LS-ICA방법이 기존의 방법에 비하여 높은 인식성능을 보였으며, 특히 오클루전이나 국부적인 변형이 포함된 얼굴영상에서 뛰어난 인식성능을 보였다.

A novel hybrid method for robust infrared target detection

  • Wang, Xin;Xu, Lingling;Zhang, Yuzhen;Ning, Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권10호
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    • pp.5006-5022
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    • 2017
  • Effect and robust detection of targets in infrared images has crucial meaning for many applications, such as infrared guidance, early warning, and video surveillance. However, it is not an easy task due to the special characteristics of the infrared images, in which the background clutters are severe and the targets are weak. The recent literature demonstrates that sparse representation can help handle the detection problem, however, the detection performance should be improved. To this end, in this text, a hybrid method based on local sparse representation and contrast is proposed, which can effectively and robustly detect the infrared targets. First, a residual image is calculated based on local sparse representation for the original image, in which the target can be effectively highlighted. Then, a local contrast based method is adopted to compute the target prediction image, in which the background clutters can be highly suppressed. Subsequently, the residual image and the target prediction image are combined together adaptively so as to accurately and robustly locate the targets. Based on a set of comprehensive experiments, our algorithm has demonstrated better performance than other existing alternatives.

Role of Online Reviews in the Local Search Context

  • Seunghun Shin;Zheng Xiang;Florian Zach
    • Journal of Smart Tourism
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    • 제3권3호
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    • pp.29-40
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    • 2023
  • This research aims to understand the role of online reviews in the local search context by examining the effects of reviews on the representation of tourism businesses on local search platforms (LSPs). By simulating tourists' local searches for restaurants on three LSPs, namely Google, Bing, and Yelp, this study examines how different ranking results are generated across the platforms and how online reviews contribute to the differences. The findings suggest that online reviews are incorporated into LSPs as ranking factors and, thus, affect tourists' decision-making by influencing the information search results in the local search context. As one of the earliest studies on local search, this study discusses how the existing knowledge about the role of online reviews in tourists' decision-making needs to be reevaluated in mobile and more dynamic environments, and offers practical implications for tourism businesses' search engine marketing.

Robust Face Recognition under Limited Training Sample Scenario using Linear Representation

  • Iqbal, Omer;Jadoon, Waqas;ur Rehman, Zia;Khan, Fiaz Gul;Nazir, Babar;Khan, Iftikhar Ahmed
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권7호
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    • pp.3172-3193
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    • 2018
  • Recently, several studies have shown that linear representation based approaches are very effective and efficient for image classification. One of these linear-representation-based approaches is the Collaborative representation (CR) method. The existing algorithms based on CR have two major problems that degrade their classification performance. First problem arises due to the limited number of available training samples. The large variations, caused by illumintion and expression changes, among query and training samples leads to poor classification performance. Second problem occurs when an image is partially noised (contiguous occlusion), as some part of the given image become corrupt the classification performance also degrades. We aim to extend the collaborative representation framework under limited training samples face recognition problem. Our proposed solution will generate virtual samples and intra-class variations from training data to model the variations effectively between query and training samples. For robust classification, the image patches have been utilized to compute representation to address partial occlusion as it leads to more accurate classification results. The proposed method computes representation based on local regions in the images as opposed to CR, which computes representation based on global solution involving entire images. Furthermore, the proposed solution also integrates the locality structure into CR, using Euclidian distance between the query and training samples. Intuitively, if the query sample can be represented by selecting its nearest neighbours, lie on a same linear subspace then the resulting representation will be more discriminate and accurately classify the query sample. Hence our proposed framework model the limited sample face recognition problem into sufficient training samples problem using virtual samples and intra-class variations, generated from training samples that will result in improved classification accuracy as evident from experimental results. Moreover, it compute representation based on local image patches for robust classification and is expected to greatly increase the classification performance for face recognition task.

Multi-feature local sparse representation for infrared pedestrian tracking

  • Wang, Xin;Xu, Lingling;Ning, Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권3호
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    • pp.1464-1480
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    • 2019
  • Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.