• Title/Summary/Keyword: detail descriptor

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Robust HDR Video Synthesis Using Illumination Invariant Descriptor (밝기 변화에 강인한 특징 기술자를 이용한 고품질 HDR 동영상 합성)

  • Vo Van, Tu;Lee, Chul
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2017.06a
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    • pp.83-84
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    • 2017
  • We propose a novel high dynamic range (HDR) video synthesis algorithm from alternatively exposed low dynamic range (LDR) videos. We first estimate correspondences between input fames using an illumination invariant descriptor. Then, we synthesize an HDR frame with the weights computed to maximize detail preservation in the output HDR frame. Experimental results demonstrate that the proposed algorithm provides high-quality HDR videos without noticeable artifacts.

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

  • Kim, Kyeong Tae;Choi, Jae Young
    • Journal of Korea Multimedia Society
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    • v.20 no.5
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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.

A study on image region analysis and image enhancement using detail descriptor (디테일 디스크립터를 이용한 이미지 영역 분석과 개선에 관한 연구)

  • Lim, Jae Sung;Jeong, Young-Tak;Lee, Ji-Hyeok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.6
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    • pp.728-735
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    • 2017
  • With the proliferation of digital devices, the devices have generated considerable additive white Gaussian noise while acquiring digital images. The most well-known denoising methods focused on eliminating the noise, so detailed components that include image information were removed proportionally while eliminating the image noise. The proposed algorithm provides a method that preserves the details and effectively removes the noise. In this proposed method, the goal is to separate meaningful detail information in image noise environment using the edge strength and edge connectivity. Consequently, even as the noise level increases, it shows denoising results better than the other benchmark methods because proposed method extracts the connected detail component information. In addition, the proposed method effectively eliminated the noise for various noise levels; compared to the benchmark algorithms, the proposed algorithm shows a highly structural similarity index(SSIM) value and peak signal-to-noise ratio(PSNR) value, respectively. As shown the result of high SSIMs, it was confirmed that the SSIMs of the denoising results includes a human visual system(HVS).

Prediction of retention of uncharged solutes in nanofiltration by means of molecular descriptors

  • Nowaczyk, Alicja;Nowaczyk, Jacek;Koter, Stanislaw
    • Membrane and Water Treatment
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    • v.1 no.3
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    • pp.181-192
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    • 2010
  • A linear quantitative structure-property relationship (QSPR) model is presented for the prediction of rejection in permeation through membrane. The model was produced by using the multiple linear regression (MLR) technique on the database consisting of retention data of 25 pesticides in 4 different membrane separation experiments. Among the 3224 different physicochemical, topological and structural descriptors that were considered as inputs to the model only 50 were selected using several criteria of elimination. The physical meaning of chosen descriptor is discussed in detail. The accuracy of the proposed MLR models is illustrated using the following evaluation techniques: leave-one-out cross validation procedure, leave-many-out cross validation procedure and Y-randomization.

The Analysis of Visual Descriptors for Content-based Video Retrieval (내용기반 비디오 검색을 위한 MPEG-7 비주얼 디스크립터 분석)

  • Kim, Seong-Hee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.16 no.2
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    • pp.157-175
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    • 2005
  • The main purpose of this paper is to explain and analyze visual descriptors of MPEG-7 for representing multimedia content. This study describes MPEG-7 visual descriptors that are made of color, shape, texture, and motion using some examples and application areas in detail. As a result, those visual descriptors can represent the rich and deep features in multimedia contents domain. Also, the use of those descriptors will increase the retrieval effectiveness as well as the interoperability among systems through the consistency of the content representation.

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