• Title/Summary/Keyword: Local Projection method

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Two-wheelers Detection using Uniform Local Binary Pattern for Projection Vectors (투영 벡터의 단일 이진패턴 가중치을 이용한 이륜차 검출)

  • Lee, Yeunghak
    • Journal of Korea Multimedia Society
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    • v.18 no.4
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    • pp.443-451
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    • 2015
  • In this paper we suggest a new two-wheelers detection algorithm using uniform local binary pattern weighting value for projection vectors. The first, we calculate feature vectors using projection method which has robustness for rotation invariant and reducing dimensionality for each cell from origin image. The second, we applied new weighting values which are calculated by the modified local binary pattern showing the fast compute and simple to implement. This paper applied the Adaboost algorithm to make a strong classification from weak classification. In this experiment, we can get the result that the detection rate of the proposed method is higher than that of the traditional method.

Estimation of Nonlinear Impulse Responses of Stock Indices by Asset Class

  • Chang, Young-Jae
    • The Korean Journal of Applied Statistics
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    • v.25 no.2
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    • pp.239-249
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    • 2012
  • We estimate nonlinear impulse responses of stock indices by asset class by the Local Projection method as suggested by Jorda (2005) to compute impulse responses. The method estimates impulse responses without the specification and estimation of the underlying multivariate dynamic system unlike the usual way of vector autoregression(VAR). It estimates Local Projections at each period of interest rather than extrapolating into increasingly distant horizons with the advantages of easy estimation and non-linear flexible specification. The Local Projection method adequately captures the nonlinearity and asymmetry of the impulse responses of the stock indices compared to those from VARs.

A new hybrid optimization algorithm based on path projection

  • Gharebaghi, Saeed Asil;Ardalan Asl, Mohammad
    • Structural Engineering and Mechanics
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    • v.65 no.6
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    • pp.707-719
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    • 2018
  • In this article, a new method is introduced to improve the local search capability of meta-heuristic algorithms using the projection of the path on the border of constraints. In a mathematical point of view, the Gradient Projection Method is applied through a new approach, while the imposed limitations are removed. Accordingly, the gradient vector is replaced with a new meta-heuristic based vector. Besides, the active constraint identification algorithm, and the projection method are changed into less complex approaches. As a result, if a constraint is violated by an agent, a new path will be suggested to correct the direction of the agent's movement. The presented procedure includes three main steps: (1) the identification of the active constraint, (2) the neighboring point determination, and (3) the new direction and step length. Moreover, this method can be applied to some meta-heuristic algorithms. It increases the chance of convergence in the final phase of the search process, especially when the number of the violations of the constraints increases. The method is applied jointly with the authors' newly developed meta-heuristic algorithm, entitled Star Graph. The capability of the resulted hybrid method is examined using the optimal design of truss and frame structures. Eventually, the comparison of the results with other meta-heuristics of the literature shows that the hybrid method is successful in the global as well as local search.

Pose Identification Using Isometric Projection

  • Islam, Ihtesham-Ul;Kim, In-Taek
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.979-980
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    • 2008
  • In this paper we use the Isometric Projection, a linear subspace method, for manifold representation of the pose-varying-faces. Isometric Projection method for pose identification is evaluated on view varying faces and is compared with other global and local linear subspace methods.

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Projected Local Binary Pattern based Two-Wheelers Detection using Adaboost Algorithm

  • Lee, Yeunghak;Kim, Taesun;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.1 no.2
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    • pp.119-126
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    • 2014
  • We propose a bicycle detection system riding on people based on modified projected local binary pattern(PLBP) for vision based intelligent vehicles. Projection method has robustness for rotation invariant and reducing dimensionality for original image. The features of Local binary pattern(LBP) are fast to compute and simple to implement for object recognition and texture classification area. Moreover, We use uniform pattern to remove the noise. This paper suggests that modified LBP method and projection vector having different weighting values according to the local shape and area in the image. Also our system maintains the simplicity of evaluation of traditional formulation while being more discriminative. Our experimental results show that a bicycle and motorcycle riding on people detection system based on proposed PLBP features achieve higher detection accuracy rate than traditional features.

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Face Recognition Robust to Local Distortion Using Modified ICA Basis Image

  • Kim Jong-Sun;Yi June-Ho
    • Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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    • 2006.06a
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    • pp.251-257
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    • 2006
  • The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. We propose an effective part-based local representation method named locally salient ICA (LS-ICA) method for face recognition that is robust to local distortion and partial occlusion. The LS-ICA method only employs locally salient information from important facial parts in order to maximize the benefit of applying the idea of 'recognition by parts.' It creates part-based local basis images by imposing additional localization constraint in the process of computing ICA architecture I basis images. We have contrasted the LS-ICA method with other part-based representations such as LNMF (Localized Non-negative Matrix Factorization)and LFA (Local Feature Analysis). Experimental results show that the LS-ICA method performs better than PCA, ICA architecture I, ICA architecture II, LFA, and LNMF methods, especially in the cases of partial occlusions and local distortion

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Two-wheeler Detection using the Local Uniform Projection Vector based on Curvature Feature (이진 단일 패턴과 곡률의 투영벡터를 이용한 이륜차 검출)

  • Lee, Yeunghak;Kim, Taesun;Shim, Jaechang
    • Journal of Korea Multimedia Society
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    • v.18 no.11
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    • pp.1302-1312
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    • 2015
  • Recent research has been devoted and focused on detecting pedestrian and vehicle in intelligent vehicles except for the vulnerable road user(VRUS). In this paper suggest a new projection method which has robustness for rotation invariant and reducing dimensionality for each cell from original image to detect two-wheeler. We applied new weighting values which are calculated by maximum curvature containing very important object shape features and uniform local binary pattern to remove the noise. This paper considered the Adaboost algorithm to make a strong classification from weak classification. Experiment results show that the new approach gives higher detection accuracy than of the conventional method.

Image Feature Extraction Using Energy field Analysis (에너지장 해석을 통한 영상 특징량 추출 방법 개발)

  • 김면희;이태영;이상룡
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.10a
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    • pp.404-406
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    • 2002
  • In this paper, the method of image feature extraction is proposed. This method employ the energy field analysis, outlier removal algorithm and ring projection. Using this algorithm, we achieve rotation-translation-scale invariant feature extraction. The force field are exploited to automatically locate the extrema of a small number of potential energy wells and associated potential channels. The image feature is acquired from relationship of local extrema using the ring projection method.

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Restoration of Chest X-ray Image Using Dual Projection Filter (이중 프로젝션 필터를 이용한 흉부 X-선 영상의 복원)

  • 이태수;민병구
    • Journal of Biomedical Engineering Research
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    • v.13 no.1
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    • pp.25-32
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    • 1992
  • A new restoration method of chest X -ray image (dual project filter) was proposed to improve SNR(signal to noise ratio) characteristics. In this method, a priori Information of system and anatomical structure and statistics of projected object are used in the design of filter. Dual projection filter varies its parameters, adapting to the local regions of chest(lung region, mediasternum, subdiaphragm) and the structure of chest (bone, tissue, blood vessel, bronchia). The performance of Dual Projection Filter was 0.1-0.2dB better than Dual Sensor Wiener Filter, which was used for initial estimate of Dual Porjection Filter.

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Population Projections for Local Governments in Korea: Based on Hamilton-Perry & Auto Regression

  • Lee, Sang-Bock
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.955-961
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    • 2007
  • Population projections provides useful basic information for the need of economic resources and labor forces. The National Office of Statistics(NSO) presents population projections for the whole country and some of higher level local governments, but not do projections of the lower level local governments. Here are some projection methods as Hamilton-Perry methods and modified auto regression methods, which are compared to cohort method published by NSO in case of Daegu metropolitan city. The simulation results are a little stagnant with modified auto regression, but a little declines are shown with NSO and HP method, for 2010, 2015 and 2020 year, respectively.

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