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检索条件"任意字段=Pacific Rim Symposium on Image and Video Technology"

共 601 条记录，以下是31-40 订阅

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image enlargement with lost high-frequency components estimation using clustered eigenspace-BPLP

Image enlargement with lost high-frequency components estima...

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pacific rim symposium on image and video technology

作者： Orii, Hideaki Kawano, Hideaki Suetake, Noriaki Maeda, Hiroshi Graduate School of Engineering Kyushu Institute of Technology Kitakyushu-city Fukuoka 804-8550 Japan Faculty of Engineering Kyushu Institute of Technology Kitakyushu-city Fukuoka 804-8550 Japan Graduate School of Science and Engineering Yamaguchi University Yamaguchi-city Yamaguchi 753-8512 Japan

ISBN: (纸本)9780769542850

In this paper, in order to realize the image enlargement with high performance, we propose a new enlargement method, which restores high-frequency components lost in the interpolation-based methods, by using high-frequency estimation. The estimation is based on the eigenspace method proposed by Amano et al.. The proposed enlargement method can generate lost high-frequency components by using pairs of low- and high-frequency components of the original image, and is referred as back projection for lost high-frequency components. Experimental results show the proposed method can achieve promising enlargement. © 2010 IEEE.

关键词： Frequency estimation

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On digital image representation by the delaunay triangulation

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2nd IEEE pacific rim symposium on video and technology

作者： Kohout, Josef Univ W Bohemia Dept Comp Sci & Engn Plzen 30614 Czech Republic

ISBN: (纸本)9783540771289

This paper deals with a transformation of raster grey-scale images into a geometric representation by the Delaunay triangulation. It discusses the influence of image filtering techniques and methods for the evaluation of significance of pixels on the conversion process. Furthermore, it proposes several novel approaches for a compression of the Delaunay triangulation and compares them with existing solutions.

关键词： image coding Delaunay triangulation compression

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Depth-based analyses of landscape paintings and photographs according to Itten's contrasts

Depth-based analyses of landscape paintings and photographs ...

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pacific rim symposium on image and video technology

作者： Constable, Martin Zhang, Xiaoyan School of Art Design and Media Nanyang Technological University Singapore 639798 Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore

ISBN: (纸本)9780769542850

Using Itten's Color Contrasts as a starting point, we performed a depth-based analysis of a set of paintings by the Hudson River school of landscape painters. This was compared to a similar analyses of a collection of contemporary 'snap shot' landscape photographs. Differences between the two groups were observed with the paintings being clearly more organized. This organization of contrasts can be considered a style that is representative of a school of painters. Photographs or optically acquired imagery can be rendered according to this organization to acquire an aesthetic that has been informed by this style. © 2010 IEEE.

关键词： image analysis

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Shape matching by region grouping

Shape matching by region grouping

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pacific rim symposium on image and video technology

作者： Gao, Yan Yau, Wei-Yun Singapore Singapore

ISBN: (纸本)9780769542850

In this paper, we propose a novel region grouping approach to shape matching. It is proposed as an alternative region based approach to the traditional edge based shape matching using distance transforms. It has the advantage of obtaining a higher detection rate and obtaining meaningful object segmentation simultaneously. Each image is first segmented into image regions, and possible matches are found among the regions based on a proposed probabilistic similarity measure to the exemplars. We evaluate this new approach against edge based matching using Chamfer and Hausdorff distances. Pros and cons of the proposed method are discussed. © 2010 IEEE.

关键词： Chamfer distance Gaussian process Hausdorff distance detection rate distance transform edge based shape matching edge detection image matching image region grouping image segmentation image segmentation object segmentation probabilistic similarity measure region grouping shape matching shape recognition transforms

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Robust motion-compensated orthogonal video coding using EBCOT

Robust motion-compensated orthogonal video coding using EBCO...

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pacific rim symposium on image and video technology

作者： Barry, Ousmane Liu, Du Richter, Stefan Flierl, Markus KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9780769542850

This paper proposes a rate-distortion control for motion-compensated orthogonal video coding schemes and evaluates its robustness to packet loss as faced in, e.g., IP networks. The robustness of standard hybrid video coding is extensively studied in the literature. In contrast, motion-compensated orthogonal subbands offer important advantages and new features for robust video transmission. In this work, we utilize so-called uni-directional motion-compensated orthogonal transforms in combination with entropy coding similar to EBCOT known from JPEG2000. The approach provides a flexible embedded structure and allows flexible rate-distortion optimization. Moreover, it may even permit separate encoding and rate control. The proposed rate-distortion control takes channel coding into account and obtains a preemptively protected representation. Our implementation is based on repetition codes, adapted to the channel condition, and improves the PSNR significantly. The optimization requires an estimate of the packet loss rate at the encoder and shows moderate sensitivity to estimation errors. © 2010 IEEE.

关键词： image coding

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A perceptually lossless image compression scheme based on JND refinement by neural network

A perceptually lossless image compression scheme based on JN...

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pacific rim symposium on image and video technology

作者： Lie, Wen-Nung Liu, Wen-Ching Department of Electrical Engineering National Chung Cheng University Chia-Yi Taiwan

ISBN: (纸本)9780769542850

In this paper, we propose a JND (Just Notice Distortion)-lossless image compression scheme that can improve the compression performance for JPEG-LS, while maintaining the image perceptual quality simultaneously. JND-lossless can be easily achieved by setting the quantization step size (QSS) to be double the JND value. However, dynamic JNDs make the coding of varying QSSs difficult and the JND estimated at decoder is often inaccurate due to incomplete background information therein. Here, we propose to use a neural classifier at both the encoder and decoder to correct the JND mismatch and make the coding of varying QSSs unnecessary. Experiments show that our proposed JND-refinement scheme is capable of increasing the compression performance by up to 15% (w.r.t. JPEG-LS) and the proposed neural classifier is capable of correcting 94% of JND mismatch. © 2010 IEEE.

关键词： Decoding

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Mash-up approach for web video category recommendation

Mash-up approach for web video category recommendation

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pacific rim symposium on image and video technology

作者： Song, Yi-Cheng Li, Haojie Institute of Computing Technology Chinese Academy of Sciences 100080 Beijing China School of Software Dalian University of Technology 116620 Dalian Liaoning China Graduate University of the Chinese Academy of Sciences 100080 Beijing China

ISBN: (纸本)9780769542850

With the advent of web 2.0, billions of videos are now freely available online. Meanwhile, rich user generated information for these videos such as tags and online encyclopedia offer us a chance to enhance the existing video analysis technologies. In this paper, we propose a mash-up framework to realize video category recommendation by leveraging web information from different sources. Under this framework, we build a web video dataset from the YouTube API, and construct a concept collection for web video category recommendation (CCWV-CR) from this dataset, which consists of the web video concepts with small semantic gap and high categorization distinguishability. Besides, Wikipedia Propagation is proposed to optimize the video similarity measurement. The experiments on the large-scale dataset with 80,031 web videos demonstrate that: (1) the mash-up category recommendation framework has a great improvement than the existing state-of-art methods. (2) CCWV-CR is an efficient feature space for video category recommendation. (3) Wikipedia Propagation could boost the performance of video category recommendation. © 2010 IEEE.

关键词： Semantics

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Optimal training set selection for video annotation

Optimal training set selection for video annotation

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pacific rim symposium on image and video technology

作者： Hong, Guo-Xiang Huang, Chung-Lin Hsu, Shih-Chung Tsai, Chi-Hung Institute of Electrical Engineering National Tsin Hua University Hsin-Chu Taiwan IDEAS Institute Institute for Information Industry Taipei Taiwan

ISBN: (纸本)9780769542850

Most learning-based video semantic analysis methods require a large training set to achieve good performances. However, annotating a large video is labor-intensive. This paper introduces how to construct the training set and reduce user involvement. There are four selection schemes proposed: clustering-based, spatial dispersiveness, temporal dispersiveness, and sample-based which can be used construct a small size and effective training set. If the selected training data can represent the characteristic of the whole video data, the classification performance will be better even when the size of the training set is smaller than that of the whole video data. To verify the best selected samples for training a semantic model, we use SVM to classify the category of the test samples. Five different categories: person, landscape, cityscape, map and others are tested. Experimental results show that these methods are effective for training set selection in video annotation, and outperform random selection. © 2010 IEEE.

关键词： Semantics

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A level-set based tracking approach for surveillance video with fusion and occlusion

A level-set based tracking approach for surveillance video w...

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pacific rim symposium on image and video technology

作者： Hong, Chaoqun Li, Na Song, Mingli Bu, Jiajun Chen, Chun Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Zhejiang University Hangzhou China

ISBN: (纸本)9780769542850

Traditional level-set-based methods of tracking contours suffered from occlusion and fusion. In this paper, the proposed method introduces dynamic incident detection to find and handle occlusion and fusion. Color histogram of the hue component in HSV color space is used to identify the objects re-entering after occlusion. On the other hand, object features including the size and the motion pattern are utilized to remove the fake regions that are fused with the object region. Besides, a comprehensive foreground extraction (CFE) method based on the combination of background subtraction and Local Binary Pattern (LBP) is proposed. It is fast and robust. Our method is Experiments show that the proposed approach outperforms previous methods on both speed and subjective quality. © 2010 IEEE.

关键词： Local binary pattern

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High-quality non-blind image deconvolution

High-quality non-blind image deconvolution

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pacific rim symposium on image and video technology

作者： Lee, Jong-Ho Ho, Yo-Sung 261 Cheomdan-gwagiro Buk-gu Gwangju 500-712 Korea Republic of

ISBN: (纸本)9780769542850

The most annoying artifacts in image deconvolution are ringing and amplified noise. These artifacts can be reduced significantly by regularization using the Maximum a Posteriori (MAP) method that exploits not only the likelihood but also the image prior in image deconvolution. Although ringing and noise can be reduced significantly with strong regularization, image details are also reduced, so the deconvolved image is neither sharp nor clear. In this paper, we propose a non-blind image deconvolution method with adaptive regularization that can reduce ringing and noise more noticeable in a smooth region and preserve image details in a textured region. For adaptive regularization, after we make a quick estimate of the reference image that can indicate the strength of regularization, we perform regularization adaptively according to the local characteristics. Experimental results show that ringing and noise are suppressed significantly, while preserving image details effectively. © 2010 IEEE.

关键词： MAP method adaptive regularization adaptive regularization amplified noise deconvolution high-quality nonblind image deconvolution image denoising image texture image texture maximum a posteriori maximum a posteriori method maximum likelihood estimation non-blind image deconvolution ringing noise

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