{"title":"Compressive sampling of LIDAR: Full-waveforms as signals of finite rate of innovation","authors":"J. Castorena, C. Creusere","doi":"10.5281/ZENODO.52084","DOIUrl":"https://doi.org/10.5281/ZENODO.52084","url":null,"abstract":"The 3D imaging community has begun a transition to full-waveform (FW) LIDAR systems which image a scene by emitting laser pulses in a particular direction and capturing the entire temporal envelope of each echo. By scanning a region, connected 1D profile waveforms of the 3D scenes can be readily obtained. In general, FW systems capture more detailed physical information and characteristic properties of the 3D scenes versus conventional 1st and 2nd generation LIDARs which simply store clouds of range points. Unfortunately, the collected datasets are very large, making tasks like processing, storage, and transmission far more resource-intensive. Current compression approaches addressing these issues rely on collecting large amounts of data and then analyzing it to identify perceptual and statistical redundancies which are subsequently removed. Collecting large amounts of data just to discard most of it is highly inefficiently. Our approach to LIDAR compression models FW return pulses as signals with finite rate of innovation (FRI). We show in this paper that sampling can be performed at the rate of innovation while still achieving good quality reconstruction. Specifically, we show that efficient sampling and compression can be achieved on actual LIDAR FW's within the FRI framework.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116671575","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}
{"title":"Video-aware MIMO precoding with packet prioritization and unequal modulation","authors":"A. Khalek, C. Caramanis, R. Heath","doi":"10.5281/ZENODO.42784","DOIUrl":"https://doi.org/10.5281/ZENODO.42784","url":null,"abstract":"Video streaming over wireless networks can achieve large quality and capacity gains from transmission techniques that are aware of the video content. This paper proposes modifying conventional multiple-input multiple-output (MIMO) systems to realize these gains by introducing video-aware PHY layer decisions. Specifically, a new PHY layer packet prioritization method is introduced that splits video data among spatial streams based on the packet loss visibility and per-stream SNRs. The objective is to maximize throughput weighted by packet loss visibility, a metric coined perceived throughput. The globally-optimal splitting policy among streams is derived. Furthermore, unequal modulation per stream is proposed and visibility-based packet dropping is optimized to satisfy delay constraints. We derive the gains vs. conventional MIMO precoding and prove that the gain is the throughput averaged over streams divided by the throughput of the worst stream.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123879188","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}
{"title":"A geometrical stopping criterion for the LAR algorithm","authors":"C. Valdman, M. Campos, J. A. Apolinário","doi":"10.5281/ZENODO.42752","DOIUrl":"https://doi.org/10.5281/ZENODO.42752","url":null,"abstract":"In this paper a geometrical stopping criterion for the Least Angle Regression (LAR) algorithm is proposed based on the angles between each coefficient data vector and the residual error. Taking into account the most correlated coefficients one by one, the LAR algorithm can be interrupted to estimate a given number of non-zero coefficients. However, if the number of coefficients is not known a priori, defining when to stop the LAR algorithm is an important issue, specially when the number of coefficients is large and the system is sparse. The proposed scheme is validated employing the LAR algorithm with a Volterra filter to identify nonlinear systems of third and fifth orders. Results are compared with three other criteria: Akaike Information, Schwarz's Bayesian Information, and Mallows Cp.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121482341","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}
{"title":"Camera model identification Based on hypothesis testing theory","authors":"T. H. Thai, R. Cogranne, F. Retraint","doi":"10.5281/ZENODO.52444","DOIUrl":"https://doi.org/10.5281/ZENODO.52444","url":null,"abstract":"This paper aims to study the problem of imaging device identification using the heteroscedastic property of uncompressed image noise. Noise variance depends on pixels intensity through two parameters which uniquely represent a camera model and hence, enable to identify imaging device. The decision problem is cast in the framework of hypothesis testing theory. First, the theoretical context in which both the inspected image parameters and imaging device properties are known is considered. The most powerful Likelihood Ratio Test (LRT) is presented and its detection performance is analytically calculated. Then, the practical situation when inspected image parameters are unknown, but imaging device properties remain known, is studied. Based on a simple yet efficient image model, the inspected image parameters are estimated. This leads to the designed Generalized Likelihood Ratio Test (GLRT) whose statistical performances are analytically given. Numerical simulations and experimentations on natural images show the relevance of the proposed approach.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125231286","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}
Abdalbassir Abou-Elailah, F. Dufaux, J. Farah, Marco Cagnazzo
{"title":"Fusion of global and local side information using Support Vector Machine in transform-domain DVC","authors":"Abdalbassir Abou-Elailah, F. Dufaux, J. Farah, Marco Cagnazzo","doi":"10.5281/ZENODO.43270","DOIUrl":"https://doi.org/10.5281/ZENODO.43270","url":null,"abstract":"Side information has a strong impact on the performance of Distributed Video Coding. Commonly, side information is generated using motion compensated temporal interpolation. In this paper, we propose a new method for the fusion of global and local side information using Support Vector Machine. The global side information is generated at the decoder using global motion parameters estimated at the encoder using the Scale-Invariant Feature Transform. Experimental results show that the proposed approach can achieve a PSNR improvement of up to 1.7 dB for a GOP size of 2 and up to 3.78 dB for larger GOP sizes, with respect to the reference DISCOVER codec.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125633104","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}
{"title":"Distributed GSC beamforming using the relative transfer function","authors":"S. M. Golan, S. Gannot, I. Cohen","doi":"10.5281/ZENODO.52436","DOIUrl":"https://doi.org/10.5281/ZENODO.52436","url":null,"abstract":"A speech enhancement algorithm in a noisy and reverberant enclosure for a wireless acoustic sensor network (WASN) is derived. The proposed algorithm is structured as a two stage beamformers (BFs) scheme, where the outputs of the first stage are transmitted in the network. Designing the second stage BF requires estimating the desired signal components at the transmitted signals. The contribution here is twofold. First, in spatially static scenarios, the first stage BFs are designed to maintain a fixed response towards the desired signal. As opposed to competing algorithms, where the response changes and repeated estimation thereof is required. Second, the proposed algorithm is implemented in a generalized side-lobe canceler (GSC) form, separating the treatment of the desired speech and the interferences and enabling a simple time-recursive implementation of the algorithm. A comprehensive experimental study demonstrates the equivalent performance of the centralized GSC and of the proposed algorithm for both narrowband and speech signals.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131156457","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}
{"title":"An ICA-based RFS approach for DOA tracking of unknown time-varying numberof sources","authors":"A. Masnadi-Shirazi, B. Rao","doi":"10.5281/ZENODO.43166","DOIUrl":"https://doi.org/10.5281/ZENODO.43166","url":null,"abstract":"Methods based on frequency-domain independent component analysis (ICA) in junction with state coherence transform (SCT) have been shown to be robust for extracting source location information like direction of Arrival (DOA) in highly reverberant environments and in the presence of spatial aliasing. Also, by exploiting the frequency sparsity of the sources, such methods have proven to be effective when the number of simultaneous sources is larger than the number of microphones. In many real world problems the number of concurrent speakers is unknown and varies with time as new speakers can appear and existing speakers can disappear or undergo silence periods. In order to deal with this challenging scenario of unknown time-varying number of speakers, we propose the use of the probability hypothesis density (PHD) filter which is based on random finite sets (RFS), where the multi-target states and the number of targets are integrated to form a set-valued variable. The tracking capabilities of the proposed method is demonstrated using simulations of multiple sources in reverberant environments.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133240648","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}
{"title":"Coordinated scheduling and beamforming for multicell spectrum sharing networks using branch & bound","authors":"Lei Yu, E. Karipidis, E. Larsson","doi":"10.5281/ZENODO.43261","DOIUrl":"https://doi.org/10.5281/ZENODO.43261","url":null,"abstract":"We consider the downlink of a multicell network where neighboring multi-antenna base stations share the spectrum and coordinate their frequency and spatial resource allocation strategies to improve the overall network performance. The objective of the coordination is to maximize the number of users that can be scheduled, meeting their quality-of-service requirements with the minimum total transmit power. The coordinated scheduling and multiuser transmit beamforming problem is combinatorial; we formulate it as a mixed-integer second-order cone program and propose a branch & bound algorithm that yields the optimal solution with relatively low-complexity. The algorithm can be used to motivate or benchmark approximation methods and to numerically evaluate the gains due to spectrum sharing and coordination.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133271725","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}
{"title":"Daily sound recognition using a combination of GMM and SVM for home automation","authors":"M. A. Sehili, D. Istrate, B. Dorizzi, J. Boudy","doi":"10.5281/ZENODO.43299","DOIUrl":"https://doi.org/10.5281/ZENODO.43299","url":null,"abstract":"Most elderly people monitoring systems include the detection of abnormal situations, in particular distress situations, as one of their main goals. In order to reach this objective, many solutions end up combining several modalities such as video tracking, fall detection and sound recognition, so as to increase the reliability of the system. In this work we focus on daily sound recognition as it is one of the most promising modalities. We make a comparison of two standard methods used for speaker recognition and verification: Gaussian Mixture Models (GMM) and Support Vector Machines (SVM). Experimental results show the effectiveness of the combination of GMM and SVM in order to classify sound data sequences when compared to systems based on GMM.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130345970","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}
{"title":"Statistical properties of chunkless peer-to-peer streaming systems","authors":"R. Rinaldo, R. Bernardini, R. Fabbro","doi":"10.5281/ZENODO.43235","DOIUrl":"https://doi.org/10.5281/ZENODO.43235","url":null,"abstract":"Streaming solutions based on peer-to-peer networks have recently attracted the attention of the research community, due to the fact that the possibility to exploit peers' upload bandwidth can make it possible to transmit to a large number of users at a low costs. In this paper, we analyze the packet loss probability experienced at the application layer when a stream-based, chunkless peer-to-peer network is employed. More precisely, we derive a network model that allows to characterize the asymptotic behavior of the packet loss probability when the distance between a node and the server grows. Although in the limit the packet loss probability converges to 1, we derive analytical bounds on the convergence rate, which can be used to choose network parameters so that such probability remains negligible.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114454195","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}