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2013 IEEE Global Conference on Signal and Information Processing最新文献

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Parametric dictionary learning for graph signals 图信号的参数字典学习
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736921
D. Thanou, D. Shuman, P. Frossard
{"title":"Parametric dictionary learning for graph signals","authors":"D. Thanou, D. Shuman, P. Frossard","doi":"10.1109/GlobalSIP.2013.6736921","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6736921","url":null,"abstract":"We propose a parametric dictionary learning algorithm to design structured dictionaries that sparsely represent graph signals. We incorporate the graph structure by forcing the learned dictionaries to be concatenations of subdictionaries that are polynomials of the graph Laplacian matrix. The resulting atoms capture the main spatial and spectral components of the graph signals of interest, leading to adaptive representations with efficient implementations. Experimental results demonstrate the effectiveness of the proposed algorithm for the sparse approximation of graph signals.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116871343","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: 41
Gender classification of depth images based on shape and texture analysis 基于形状和纹理分析的深度图像性别分类
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6737080
Xiaolong Wang, C. Kambhamettu
{"title":"Gender classification of depth images based on shape and texture analysis","authors":"Xiaolong Wang, C. Kambhamettu","doi":"10.1109/GlobalSIP.2013.6737080","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6737080","url":null,"abstract":"Gender classification of depth images is a challenging problem, most research work attempted to use shape information to solve this problem in the past literature. In this work, we propose a new fusion scheme for gender classification using both texture and shape features. A new ensemble scheme is advocated to combine texture and shape feature at the feature level. To evaluate the performance of our algorithm, we measure our scheme on two different datasets. The final classification result is up to 93.7% using five-fold cross validation on the whole FRGCv2 dataset, which is comparable to the classification result obtained using visible imagery.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125085504","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: 19
Adaptive dictionaries for compressive imaging 压缩成像的自适应字典
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6737070
M. Aghagolzadeh, H. Radha
{"title":"Adaptive dictionaries for compressive imaging","authors":"M. Aghagolzadeh, H. Radha","doi":"10.1109/GlobalSIP.2013.6737070","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6737070","url":null,"abstract":"Compressive imaging reconstructs the original signal by searching through the feasible space for the solution with maximum compactness under a known frame or dictionary. With the extent of available optimization tools, the recovery performance mainly relies on the power of dictionary to sparsely represent the data. Universal dictionaries can be trained from a corpus of natural images or they can be designed through mathematical modeling. However, a problem with universal dictionaries is that they are suboptimal for individual classes of images. To mitigate this suboptimality, we explore ways of adapting the dictionary after the image is sensed using local and non-overlapping sampling matrices. We demonstrate that to prevent the dictionary from becoming biased under the deterministic sensor structure, sampling matrices should have diversity across different locations of the image. The proposed dictionary adaptation along with varying sampling matrices improves the recovery over state-of-the-art universally learned dictionaries of different sizes.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"156 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128746906","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
A unified algorithmic approach to distributed optimization 分布式优化的统一算法方法
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736951
J. Mota, J. Xavier, P. Aguiar, Markus Püschel
{"title":"A unified algorithmic approach to distributed optimization","authors":"J. Mota, J. Xavier, P. Aguiar, Markus Püschel","doi":"10.1109/GlobalSIP.2013.6736951","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6736951","url":null,"abstract":"We address general optimization problems formulated on networks. Each node in the network has a function, and the goal is to find a vector x ∈ ℝn that minimizes the sum of all the functions. We assume that each function depends on a set of components of x, not necessarily on all of them. This creates additional structure in the problem, which can be captured by the classification scheme we develop. This scheme not only to enables us to design an algorithm that solves very general distributed optimization problems, but also allows us to categorize prior algorithms and applications. Our general-purpose algorithm shows a performance superior to prior algorithms, including algorithms that are application-specific.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"47 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128432346","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
Graphical models for context-aware analysis of continuous videos 连续视频上下文感知分析的图形模型
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736924
Yingying Zhu, A. Roy-Chowdhury
{"title":"Graphical models for context-aware analysis of continuous videos","authors":"Yingying Zhu, A. Roy-Chowdhury","doi":"10.1109/GlobalSIP.2013.6736924","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6736924","url":null,"abstract":"In this paper, we show how graphical models can used for the localization and recognition of activities in continuous videos. The model consists of an action layer and a hidden activity layer. The action layer is modeled as a linear-chain conditional random field (CRF) with the activity labels of action segments as the model variables. Hidden activity variables are then introduced to smooth out the activity labels of action segments and thus generating semantically meaningful activities. With a task-oriented discriminative approach, the learning problem is formulated as a latent Structural Support Vector Machine (SSVM). We show promising results on the UCLA Office Dataset that demonstrate the effectiveness of the proposed framework.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129648767","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: 1
Spectrum sensing method without the impact of noise uncertainty 不受噪声不确定性影响的频谱传感方法
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6737114
Zhe Sun, Weijia Han, Zan Li, Yan Zhang, Meilu Lin
{"title":"Spectrum sensing method without the impact of noise uncertainty","authors":"Zhe Sun, Weijia Han, Zan Li, Yan Zhang, Meilu Lin","doi":"10.1109/GlobalSIP.2013.6737114","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6737114","url":null,"abstract":"In cognitive radio, the spectrum sensing plays a key role in determining the performance of both the primary and the secondary networks. The eigenvalue based detection (EbD) algorithm has received broad attentions, since it shows significant robustness to the noise uncertainty problem. However, in EbD algorithm, it is quite difficult to obtain the distribution for the eigenvalues of the statistic covariance matrix, causing the false alarm or detection probability fail to be controlled efficiently. To this end, in this paper, we reinvestigate the eigenvalues from the perspective of the circulant matrix and propose a power spectrum density (PSD) based detection (PbD) algorithm. The proposed algorithm not only shares the same principle as the EbD algorithm, but also its error probability can be calculated efficiently. The closed-form expressions for the sensing threshold and the detection probability of our PdD algorithm are also provided. Simulation results validate our theoretical analysis well.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129828141","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
Integrated genotyping of structural variation 结构变异的综合基因分型
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736808
Xian Fan, L. Nakhleh, Ken Chen
{"title":"Integrated genotyping of structural variation","authors":"Xian Fan, L. Nakhleh, Ken Chen","doi":"10.1109/GlobalSIP.2013.6736808","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6736808","url":null,"abstract":"Discovering genotype of structural variations (SV) is a new and challenging topic. To the best of our knowledge, estimation of variant allele frequency (VAF) of an SV from both read depth and read alignment has not been done. In this study, we propose BreakDown, a new statistical model that integrates read depth, discordant and split paired-end read alignment to accurately estimate SVs' genotypes and VAFs. Application to 43 low coverage samples in the 1000 Genomes Project shows that BreakDown produces highly accurate genotypes, especially on heterozygous deletions. Estimation of VAFs on both low- and high-coverage data is shown to converge on expected values with small divergence.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129834626","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
Joint estimation of motion and arc breakpoints for scalable compression 可伸缩压缩中运动和弧线断点的联合估计
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736919
Sean I. Young, R. Mathew, D. Taubman
{"title":"Joint estimation of motion and arc breakpoints for scalable compression","authors":"Sean I. Young, R. Mathew, D. Taubman","doi":"10.1109/GlobalSIP.2013.6736919","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6736919","url":null,"abstract":"An alternative, graphical model for motion estimation (ME) is proposed for video compression using a dense motion field. Unlike other types of optical flow-based motion analysis techniques, the chief goal of our work is jointly to discover a piece-wise smooth motion field with compression-motivated regularization, where the underlying motion compression scheme has resolution and quality scalability attributes. The graphical model formulation is presented and obtained results are discussed.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127050347","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
Indian Buffet Game with non-Bayesian social learning 印度自助餐游戏与非贝叶斯社会学习
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736877
Chunxiao Jiang, Yan Chen, Yang Gao, K. Liu
{"title":"Indian Buffet Game with non-Bayesian social learning","authors":"Chunxiao Jiang, Yan Chen, Yang Gao, K. Liu","doi":"10.1109/GlobalSIP.2013.6736877","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6736877","url":null,"abstract":"How users in a dynamic system perform learning and make decision become more and more important in numerous research fields. In this paper, we propose an Indian Buffet Game to study how users in a dynamic system learn the uncertain system state and make multiple concurrent decisions by not only considering the current utility, but also taking into account the influence of subsequent users' decisions. We analyze the proposed Indian Buffet Game under two different scenarios: one is customers has budget constraint and the other is without budget constraint. For both cases, we design recursive best response algorithms to find the subgame perfect Nash equilibrium for customers. Moreover, we introduce a non-Bayesian social learning algorithm for customers to learn the system state. Finally, we conduct simulations to validate the effectiveness and efficiency of the proposed algorithms.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130627095","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
How wideband receiver nonlinearities impact spectrum sensing 宽带接收器非线性如何影响频谱感知
2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6737117
Eric Rebeiz, D. Cabric
{"title":"How wideband receiver nonlinearities impact spectrum sensing","authors":"Eric Rebeiz, D. Cabric","doi":"10.1109/GlobalSIP.2013.6737117","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6737117","url":null,"abstract":"Wideband receivers are appealing for cognitive radio spectrum sensing as they allow sensing multiple subbands in parallel. However, wideband radio front-end circuits introduce various impairments into the received signal, which make detection of unoccupied bands difficult. In particular, the low noise amplifier and mixer are typically nonlinear components due to which the wideband received signal experiences internal mixing of the signal components, often referred to as intermodulation terms. The impact of these intermodulation terms on the wideband spectrum sensing might be significant in cases of both detection of occupied and unoccupied bands. In particular, energy detection based spectrum sensing might result in high false alarm probability due to increased energy in the band of interest due to intermodulation terms. In this paper we analyze the impact of LNA and mixer nonlinearities on energy detection based spectrum sensing, and show that although both components result in intermodulation terms in different subbands of the wideband channel, they both result in severe degradation of the spectrum sensing performance. We also discuss possible digital signal processing algorithms for compensation of nonlinearities.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130662520","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: 9
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