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A robust multivariate reranking algorithm for Question Answering enrichment 一种鲁棒的多变量问答浓缩再排序算法
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467260
Yang Liu, Jie Liu, Dong Wang, Jian Cheng
{"title":"A robust multivariate reranking algorithm for Question Answering enrichment","authors":"Yang Liu, Jie Liu, Dong Wang, Jian Cheng","doi":"10.1109/ICIP.2012.6467260","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467260","url":null,"abstract":"Cognitive research indicates that multimedia information have benefits over text-only information by means of intuitive and vivid expression. In this paper, we introduce a novel multimedia Question Answering approach to enrich text answers with image and video information. Especially, we propose a robust multivariate reranking algorithm which adopts a squared hinge loss function for learning ranking functions from preference information. Given a question and the community-contributed answer, our approach determines whether it should perform enrichment, for which a list of relevant and high-quality web-scale multimedia data are enriched and ranked automatically by reranking algorithm. Different from some efforts that attempt to directly use image and video data to replace text answers, enriching text in this way may be more feasible and useful to deal with more complex questions. The empirical experiments conducted on a wide variety of daily questions show the effectiveness of our approach.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125558295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Learning based alpha matting using support vector regression 使用支持向量回归的基于学习的alpha抠图
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467308
Zhanpeng Zhang, Qingsong Zhu, Yaoqin Xie
{"title":"Learning based alpha matting using support vector regression","authors":"Zhanpeng Zhang, Qingsong Zhu, Yaoqin Xie","doi":"10.1109/ICIP.2012.6467308","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467308","url":null,"abstract":"Alpha matting refers to the problem of estimating the opacity mask of the foreground in an image. Many recent algorithms solve it with color samples or some local assumptions, causing artifacts when they fail to collect appropriate samples or the assumptions do not hold. In this paper, we treat alpha matting as a supervised learning problem and propose a new matting approach. Given the input image and a trimap (labeling some foreground/background pixels), we segment the unlabeled region into pieces and learn the relations between pixel features and alpha values for these pieces. We use support vector regression (SVR) in the learning process. To obtain better learning results, we design a training samples selection method and use adaptive parameters for SVR. Qualitative and quantitative evaluations on a matting benchmark show that our approach outperforms many recent algorithms in terms of accuracy.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"29 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115990335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 24
Learning to rerank images with enhanced spatial verification 学习重新排序图像与增强的空间验证
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467264
Chang Xu, Yangxi Li, Chao Zhou, Chao Xu
{"title":"Learning to rerank images with enhanced spatial verification","authors":"Chang Xu, Yangxi Li, Chao Zhou, Chao Xu","doi":"10.1109/ICIP.2012.6467264","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467264","url":null,"abstract":"Reranking is one of the commonly used schemes to improve the initial ranking performance for content based image retrieval (CBIR). The state-of-the-art reranking methods for CBIR are mainly based on spatial verification and global feature. To mine the complementary properties of different reranking strategies, we combine features representing images from different perspectives with RankSVM to obtain a reranking model to refine the initial ranking list. Besides, compared with traditional spatial verification based methods which measure image similarity only with single inlier's statistical properties, we bind close inlier visual words together to mine more geometric information from images. Through organizing inliers into sequence and computing the relative positions among inliers, we define an efficient similarity measurement with the order consistency between inlier sequences. Experimental results on both Oxford and imageNet datasets demonstrate that our proposed reranking method is effective and promising.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121605810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Targeted steganalysis of adaptive pixel-value differencing steganography 自适应像素值差分隐写术的目标隐写分析
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467063
Shunquan Tan, Bin Li
{"title":"Targeted steganalysis of adaptive pixel-value differencing steganography","authors":"Shunquan Tan, Bin Li","doi":"10.1109/ICIP.2012.6467063","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467063","url":null,"abstract":"The adaptive pixel-value differencing steganography proposed by Luo et al. is a state-of-the-art content-adaptive steganographic method which resists blind steganalytic attacks. In this paper, the authors point out that the combination of rotate operation and ternary embedding units in the adaptive pixel-value differencing steganography introduces intrinsic statistical imbalance which can be used to construct a targeted steganalytic algorithm. Experimental results reveal that the proposed method can obtain excellent results for detecting stego images even when the embedding rate is low.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127638426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Fusion of finger vein and finger dorsal texture for personal identification based on Comparative Competitive Coding 基于比较竞争编码的手指静脉和手指背纹理融合个人识别
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467066
Wenming Yang, X. Huang, Q. Liao
{"title":"Fusion of finger vein and finger dorsal texture for personal identification based on Comparative Competitive Coding","authors":"Wenming Yang, X. Huang, Q. Liao","doi":"10.1109/ICIP.2012.6467066","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467066","url":null,"abstract":"In this paper, we present a multimodal personal identification system using finger vein and finger dorsal images with their fusion applied at the feature level. A scheme which combines the registration of image pairs with the region-of-interest (ROI) segmentation, is explored on simultaneously captured finger ventral vein and finger dorsal images. We developed a “Comparative Competitive Coding” (C2Code) fusion scheme. It is capable of discarding undesired information in unimodal feature extraction stage. And only discriminative information can be preserved. Furthermore, the C2Code contains new feature of junction points from the finger vein and finger dorsal image pairs. Experimentally, we establish a dataset of finger vein and finger dorsal images. Comparing the performance of proposed fusion scheme with unimodal methods, higher identification accuracy and lower Equal-Error-Rate (EER) are achieved.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124615767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
On the nature of variational salt-and-pepper noise removal and its fast approximation 变分椒盐噪声去除的性质及其快速逼近
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467080
Y. Wan, Jiafa Zhu, Qiqiang Chen
{"title":"On the nature of variational salt-and-pepper noise removal and its fast approximation","authors":"Y. Wan, Jiafa Zhu, Qiqiang Chen","doi":"10.1109/ICIP.2012.6467080","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467080","url":null,"abstract":"So far there are two separate approaches to removing salt-and-pepper noise: the median type filtering and the variational formulation. The first approach usually has fast speed, while the latter produces greatly improved result at much slower speed. In this paper we show that the variational approach can be approximated as a region growing process and propose a novel iterative algorithm that combines the strength of these two approaches. When viewed within a single iteration, the algorithm acts like a median type filter. When viewed across iterations, the filter achieves the region growing effect accomplished by the variational approach. Extensive simulations show that the proposed algorithm achieves the state of the art performance with the fastest speed published so far. The insight gained in this paper could have broader applications.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117088212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Content-adaptive temporal consistency enhancement for depth video 深度视频的内容自适应时间一致性增强
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467535
H. Zeng, K. Ma
{"title":"Content-adaptive temporal consistency enhancement for depth video","authors":"H. Zeng, K. Ma","doi":"10.1109/ICIP.2012.6467535","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467535","url":null,"abstract":"The video plus depth format, which is composed of the texture video and the depth video, has been widely used for free viewpoint TV. However, the temporal inconsistency is often encountered in the depth video due to the error incurred in the estimation of the depth values. This will inevitably deteriorate the coding efficiency of depth video and the visual quality of synthesized view. To address this problem, a content-adaptive temporal consistency enhancement (CTCE) algorithm for the depth video is proposed in this paper, which consists of two sequential stages: (1) classification of stationary and non-stationary regions based on the texture video, and (2) adaptive temporal consistency filtering on the depth video. The result of the first stage is used to steer the second stage so that the filtering process will be conducted in an adaptive manner. Extensive experimental results have shown that the proposed CTCE algorithm can effectively mitigate the temporal inconsistency in the original depth video and consequently improve the coding efficiency of depth video and the visual quality of synthesized view.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123936796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
A variational multiphase model for simultaneous MR image segmentation and bias correction 一种同时用于MR图像分割和偏置校正的变分多相模型
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467290
Haili Zhang, Yunmei Chen, X. Ye
{"title":"A variational multiphase model for simultaneous MR image segmentation and bias correction","authors":"Haili Zhang, Yunmei Chen, X. Ye","doi":"10.1109/ICIP.2012.6467290","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467290","url":null,"abstract":"In this paper, we present a multiphase segmentation model for MR images in the presence of strong intensity inhomogeneity. The problem is formalized as a constraint min-max optimization problem that consists both primal and dual variables. We use the primal dual hybrid gradient (PDHG) algorithm to alternately solve for the optimal solutions. The proposed algorithm is quite efficient in that all the subproblems have closed form solutions. Moreover, the computational complexity is shown to be linear with respect to the size of the image. Numerical experiments on various images demonstrated that our algorithm outperforms recently developed methods in terms of efficiency and accuracy.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"332 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116444753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Bayesian image separation with natural image prior 自然图像先验的贝叶斯图像分离
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467305
Haichao Zhang, Yanning Zhang
{"title":"Bayesian image separation with natural image prior","authors":"Haichao Zhang, Yanning Zhang","doi":"10.1109/ICIP.2012.6467305","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467305","url":null,"abstract":"Image separation from a set of observed mixtures has important applications in many fields such as intrinsic image extraction. We investigate in this work a natural image prior based image separation algorithm. The natural image prior is modeled via a high-order Markov Random Field (MRF) and is integrated into a Bayesian framework for estimating all the component images. Due to the usage of the natural image prior, which typically leading to non-convex optimization problems, there is no closed form solution for estimating the component images. Therefore, a Markov chain Monte-Carlo based sampling algorithm is developed for solution. Based on this, a Minimum Mean Square Error (MMSE) estimation can be achieved. The proposed method exploits both the mixing observations and the prior distribution of natural images, modeled via an MRF model. Experimental results indicate that the proposed method can generate better results than state-of-the-art image separation algorithms.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123672097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
SIFT-based Elastic sparse coding for image retrieval 基于sift的图像检索弹性稀疏编码
International Conference on Information Photonics Pub Date : 2012-09-01 DOI: 10.1109/ICIP.2012.6467390
Jun Shi, Zhi-guo Jiang, Haoxiang Feng, Liguo Zhang
{"title":"SIFT-based Elastic sparse coding for image retrieval","authors":"Jun Shi, Zhi-guo Jiang, Haoxiang Feng, Liguo Zhang","doi":"10.1109/ICIP.2012.6467390","DOIUrl":"https://doi.org/10.1109/ICIP.2012.6467390","url":null,"abstract":"Bag-of-features (BoF) model based on SIFT generally assumes each descriptor is related to only one visual word of the codebook. Therefore, the potential correlation between the descriptor and other visual words is ignored. On the other hand, sparse coding through l1-norm regularization fails to generate optimal sparse representations since l1-norm regularization randomly selected one variable from a group of highly correlated variables. In this study we propose a novel bag-of-features model for image retrieval called SIFT-based Elastic sparse coding. The method utilizes a large number of SIFT descriptors to construct the codebook. The Elastic Net regression framework, which combines both l1-norm and l2-norm penalties, is then used to obtain the sparse-coefficient vector corresponding to the SIFT descriptor. Finally each image can be represented by a unified sparse-coefficient vector. Experimental results on Coil20 dataset demonstrate the consistent superiority of the proposed method over the state-of-the-art algorithms including original SIFT matching, conventional BoF strategy and BoF model based on l1-norm sparse coding.","PeriodicalId":147245,"journal":{"name":"International Conference on Information Photonics","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124683958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
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