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检索条件"任意字段=International Conference on Computer Vision and Image Processing, CVIP 2016"

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image Fusion Based on Region Structure Similarity and Contourlet Transform

Image Fusion Based on Region Structure Similarity and Contou...

引用

IEEE international conference on Signal and image processing (ICSIP)

作者： Gong, Jiamin Wang, Beibei Deng, Yingna Qiao, Lin Liu, Huabo Xu, Jiachi Zhang, Zhengjun Xian Univ Posts & Telecommun Sch Elect Engn Xian Shaanxi Peoples R China Xian Univ Posts & Telecommun Sch Commun & Informat Engn Xian Shaanxi Peoples R China Xian Univ Posts & Telecommun Sch Automat Xian Shaanxi Peoples R China Xian Univ Posts & Telecommun Sch Sci Xian Shaanxi Peoples R China

ISBN: (纸本)9781509023776

In order to improve the quality of fusion image integrated by infrared and visible images, so that it is more suitable for human and computer vision or processing. A two-step fusion method, that is region structure similarity and Contourlet transform, is presented. With the blocking idea, source images are fused by using region structure similarity, region energy ratio and region clarity ratio to obtain the first fusion image. Then the first fusion image and two source images are decomposed by taking Contourlet transform, and low frequency components use region variance weighting rule, high frequency components adopt multi-scale analysis. Experimental results prove that our proposed method can improve subjective visual effect of the image. Meanwhile objective evaluation indexes entropy, standard deviation, average gradient and mutual information are increased.

关键词： image fusion infrared image visible image region structure similarity contourlet transform

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LEARNING A LOW-RANK SHARED DICTIONARY FOR OBJECT CLASSIFICATION 23

LEARNING A LOW-RANK SHARED DICTIONARY FOR OBJECT CLASSIFICAT...

引用

23rd IEEE international conference on image processing (ICIP)

作者： Vu, Tiep H. Monga, Vishal Penn State Univ University Pk PA 16802 USA

ISBN: (纸本)9781467399616

Despite the fact that different objects possess distinct class specific features, they also usually share common patterns. Inspired by this observation, we propose a novel method to explicitly and simultaneously learn a set of common patterns as well as class-specific features for classification. Our dictionary learning framework is hence characterized by both a shared dictionary and particular (class-specific) dictionaries. For the shared dictionary, we enforce a low rank constraint, i.e. claim that its spanning subspace should have low dimension and the coefficients corresponding to this dictionary should be similar. For the particular dictionaries, we impose on them the well-known constraints stated in the Fisher discrimination dictionary learning (FDDL). Further, we propose a new fast and accurate algorithm to solve the sparse coding problems in the learning step, accelerating its convergence. The said algorithm could also be applied to FDDL and its extensions. Experimental results on widely used image databases establish the advantages of our method over state-of-the-art dictionary learning methods.

关键词： computer vision

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AUTOMATIC MEASUREMENT SYSTEM OF VISIBLE GREENERY RATIO USING AUGMENTED REALITY 21

AUTOMATIC MEASUREMENT SYSTEM OF VISIBLE GREENERY RATIO USING...

引用

21st international conference on computer-Aided Architectural Design Research in Asia (CAADRIA)

作者： Ding, Yakui Fukuda, Tomohiro Yabuki, Nobuyoshi Michikawa, Takashi Motamedi, Ali Osaka Univ Suita Osaka Japan

ISBN: (纸本)9789881902672

Greening has been promoted to improve the living conditions in urban environments. Quantification of greenery is an important issue to identify the criteria for stakeholders in the process of greening. This research focuses on the quantification of visible greenery ratio which is defined as the amount of greenery in the field of vision. Some measurement methods of visible greenery ratio have been already proposed. However, the quantification process is usually time consuming and prone to human errors due to manual operations by using an image processing software. Therefore, in this research, the authors developed an automated measurement system based on image processing technology for the efficient visible greenery ratio measurement. In the verification experiment, the proposed method achieved similar results for extracted pixels of green areas as the traditional manual method, with decreased calculation time. Furthermore, in addition to measuring the current ratio of greenery, this system can visualize possible future changes in visible greenery by adding planting (landscape) design models in an Augmented Reality (AR) environment. Using the proposed method, an ideal greening environment can be designed and evaluated by end-users, more intuitively. The developed design system is expected to eventually result in increasing the amount of greenery in the urban environment.

关键词： Visible greenery ratio image processing automatic measurement tool augmented reality

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The research on electronic computer games as a recreational activity in Turkey

The research on electronic computer games as a recreational ...

引用

2016 international conference on Interfaces and Human computer Interaction, IHCI 2016, Game and Entertainment Technologies, GET 2016 and computer Graphics, Visualization, computer vision and image processing, CGVcvip 2016

作者： Munusturlar, Söleyman Munusturlar, Möge Akyildiz Anadolu University Faculty of Sport Sciences Department of Recreation Turkey

ISBN: (纸本)9789898533524

Entertainment games provide engaging activities and it would appear that far from waning, interest in games for leisure is still growing. The availability of new consoles, platforms and technologies for the delivery of games is an important factor in this continued growth. The aim of this study is to determine characteristic and habits of computer game players in Turkey. In line with this purpose following processes were followed and reported. Study group of the research is chosen by random sampling method through online questionary techniques from 69 women and 252 men, 321 people in total. Two different data collection tools were used in gathering research data. As a result of the study, most of the computer game players choses target shooting games and sportive, action, and fantasy games follow to target shooting games as popularity and more than half of players (%56) prefer to play multiplayer games than single player games. It is reported that players spend approximately 10,1 hours playing computer game per week.

关键词： Leisure

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ANALYSIS OF ERROR RESILIENCY OF BELIEF PROPAGATION IN computer vision 41

ANALYSIS OF ERROR RESILIENCY OF BELIEF PROPAGATION IN COMPUT...

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41st IEEE international conference on Acoustics, Speech and Signal processing (ICASSP)

作者： Choi, Jungwook Patil, Ameya D. Rutenbar, Rob A. Shanbhag, Naresh R. IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA Univ Illinois Dept Elect & Comp Engn Champaign IL 61801 USA Univ Illinois Dept Comp Sci Champaign IL 61801 USA

ISBN: (纸本)9781479999880

Probabilistic inference is a versatile tool to solve a large variety of pixel-labeling problems in computer vision such as stereo matching and image denoising. Belief Propagation (BP) is an effective method for such inference tasks, and has also shown attractive error-resilience properties-the ability to converge to usable solutions in the presence of low-level hardware errors. This is of increasing interest, as the looming end of Moore's Law scaling brings with it a vast increase in the statistical variability of nanoscale circuit fabrics. In this work we seek to understand why certain combinations of BP and error-resilience mechanisms work so well in practice. We focus on Algorithmic Noise Tolerance (ANT) techniques for the resilience mechanisms, and Max-Product BP for inference. We analyze the error characteristics of BP in this hardware context, derive novel asymptotic error bounds, and provide theoretical reasoning to explain why ANT works well in this BP context. Experimental results from detailed resilient-BP simulations for various stereo matching tasks offer empirical support for this analysis.

关键词： Probabilistic inference algorithmic noise tolerance computer vision belief propagation

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ON THE GENERALITY OF NEURAL image FEATURES 23

ON THE GENERALITY OF NEURAL IMAGE FEATURES

引用

23rd IEEE international conference on image processing (ICIP)

作者： Venkatesan, Ragav Gatupalli, Vijetha Li, Baoxin Arizona State Univ Sch Comp Informat & Decis Syst Engn Tempe AZ 85281 USA

ISBN: (纸本)9781467399616

Often the filters learned by Convolutional Neural Networks (CNNs) from different image datasets appear similar. This similarity of filters is often exploited for the purposes of transfer learning. This is also being used as an initialization technique for different tasks in the same dataset or for the same task in similar datasets. Off-the-shelf CNN features have capitalized on this idea to promote their networks as best transferable and most general and are used in a cavalier manner in day-to-day computer vision tasks. While the filters learned by these CNNs are related to the atomic structures of the images from which they are learnt, all datasets learn similar looking low-level filters. With the understanding that a dataset that contains many such atomic structures learn general filters and are therefore useful to initialize other networks with, we propose a way to analyse and quantify generality. We applied this metric on several popular character recognition, natural image and a medical image dataset, and arrive at some interesting conclusions. On further experimentation we also discovered that particular classes in a dataset themselves are more general than others.

关键词： Character recognition

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Accelerating DCT-based color image watermarking on GPUs

Accelerating DCT-based color image watermarking on GPUs

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2016 international conference on image processing, computer vision, and Pattern Recognition, IPCV 2016

作者： Fan, Hong Huang, Miaoqing Lai, Chenggang Yu, Jinming Xu, Wujun School of Information Science and Technology Donghua University Shanghai China Department of Computer Science and Computer Engineering University of Arkansas AR United States

ISBN: (纸本)1601324421

— Watermarking is widely used to protect information authenticity and integrity. In this work we propose to add invisible watermark into one channel of color RGB images in the frequency domain. Using Discrete Cosine Transform (DCT) in watermarking can result in better watermark quality and robustness due to the use of uncorrelated coefficients that operate in the frequency domain. The watermarking process consists of three steps, i.e., DCT, adding watermark, inverse DCT (IDCT). Applying DCT/IDCT on large images using CPUs typically takes quite long time, which prevents the online integration of invisible watermarks. GPUs can significantly improve the performance of the watermarking process. In our experiments, it is found that Nvidia Tesla K20 GPU is able to add watermark to one 512×512 image in less than 0.1 ms, which is 170 times faster than the Intel Core i7-3820 CPU. The energy-efficient GPU on Tegra TK1 SOC can achieve more than 20× speedup than the ARM CPU. © CSREA Press.

关键词： Graphics processing unit

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image DESCRIPTION THROUGH FUSION BASED RECURRENT MULTI-MODAL LEARNING 23

IMAGE DESCRIPTION THROUGH FUSION BASED RECURRENT MULTI-MODAL...

引用

23rd IEEE international conference on image processing (ICIP)

作者： Oruganti, Ram Manohar Sah, Shagan Pillai, Suhas Ptucha, Raymond Rochester Inst Technol Comp Engn Rochester NY 14603 USA Rochester Inst Technol Ctr Imaging Sci Rochester NY USA Rochester Inst Technol Comp Sci Rochester NY USA

ISBN: (纸本)9781467399616

Current research in computer vision and machine learning has demonstrated some great abilities at detecting and recognizing objects in natural images. The promising results in these areas have inspired research towards solving more complex multi-modal learning problems in the image/video domains such as automatic annotation, segmentation, labelling, and generic understanding. Although solutions have been provided for one or more of these problems, their approaches have been application specific. This paper introduces an end-to-end trainable Fusion-based Recurrent Multi-Modal (FRMM) model to address multi-modal applications. FRMM allows each input modality to be independent in terms of architecture, parameters and length of input sequences. FRMM image description models seamlessly blend convolutional neural net work feature descriptors with sequential language data in a recurrent framework. For training and testing we used the Flickr30K and MSCOCO datasets, demonstrating state-of-the-art description results.

关键词： image Captioning CNN LSTM Recurrent Neural Networks

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Fast printing defects inspection based on multi-matching 12

Fast printing defects inspection based on multi-matching

引用

12th international conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016

作者： Luo, Bing Guo, Guiping School of Computer Science and Technology Wuyi University Jiangmen China

ISBN: (纸本)9781509040933

Surface printing defects inspection based on machine vision can effectively improve producing speed and quality. However, captured image rotate variance led to high false detection rate and low speed. Considering limited rotate variance, multi-templates which are rotated from normal template were set up before inspection. The mismatching object image was matched again with the rotated templates and image rotate processing is avoided during inspection. Simple logic operation accelerated inspection speed and depress false detection rate. © 2016 IEEE.

关键词： computer vision

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Epipolar Geometry Comparison of SAR and Optical Camera 2

Epipolar Geometry Comparison of SAR and Optical Camera

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2nd ISPRS international conference on computer vision in Remote Sensing (CVRS)

作者： Li, Dong Zhang, Yunhua Chinese Acad Sci Natl Space Sci Ctr Key Lab Microwave Remote Sensing 1 Nanertiao Beijing 100190 Peoples R China

ISBN: (纸本)9781510601543

In computer vision, optical camera is often used as the eyes of computer. If we replace camera with synthetic aperture radar (SAR), we will then enter a microwave vision of the world. This paper gives a comparison of SAR imaging and camera imaging from the viewpoint of epipolar geometry. The imaging model and epipolar geometry of the two sensors are analyzed in detail. Their difference is illustrated, and their unification is particularly demonstrated. We hope these may benefit researchers in field of computer vision or SAR image processing to construct a computer SAR vision, which is dedicated to compensate and improve human vision by electromagnetically perceiving and understanding the images.

关键词： computer vision computer SAR vision epipolar geometry imaging model optical camera synthetic aperture radar (SAR) 3D reconstruction

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