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2015 IEEE International Conference on Digital Signal Processing (DSP)最新文献

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Gunshot acoustic component localization with distributed circular microphone arrays 分布式圆形传声器阵列枪弹声分量定位
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-09-10 DOI: 10.1109/ICDSP.2015.7252067
S. Astapov, J. Ehala, J. Berdnikova, J. Preden
{"title":"Gunshot acoustic component localization with distributed circular microphone arrays","authors":"S. Astapov, J. Ehala, J. Berdnikova, J. Preden","doi":"10.1109/ICDSP.2015.7252067","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7252067","url":null,"abstract":"Gunshot acoustic localization for military and urban security systems has long been an important topic of research. In recent years the development of independent Unmanned Ground Sensors (UGS), interconnected through Wireless Sensor Networks (WSN), performing distributed cooperative localization, has grown in popularity. This paper considers a 2D Direction of Arrival (DOA) estimation method for compact circular array UGS, establishing gunshot direction at close range, and discusses problems, situated with gunshot acoustic component analysis. The proposed method is aimed at reducing the computational cost of DOA calculation for implementation on embedded hardware of WSN smart sensors. It is compared with the SRP-PHAT localization algorithm and is proven to provide adequate DOA estimates, while being more computationally effective.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127034215","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: 7
Analysis of the noise robustness problem and a new blind channel identification algorithm 噪声鲁棒性问题分析及一种新的盲信道识别算法
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-09-10 DOI: 10.1109/ICDSP.2015.7251994
Lei Liao, X. Li, Andy W. H. Khong, Xin Liu
{"title":"Analysis of the noise robustness problem and a new blind channel identification algorithm","authors":"Lei Liao, X. Li, Andy W. H. Khong, Xin Liu","doi":"10.1109/ICDSP.2015.7251994","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7251994","url":null,"abstract":"Blind channel identification has generated much interest in signal processing and communications. Although existing cross relation based blind channel identification algorithm can achieve promising results, one of the drawbacks is the performance degradation in a noisy environment. In this work, we show that the degradation in convergence performance of MCLMS is due to an implicit constraint imposed by the cross relation cost function. This constraint requires the estimated impulse responses to be of the same energy which is often untrue in practice. We next propose a new algorithm exploiting revised cost function to improve the robustness of MCLMS to noise. Monte Carlo simulation results show that the proposed algorithm can gain significant improvement in steady-state performance.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121672391","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
An ensemble technique for estimating vehicle speed and gear position from acoustic data 基于声学数据估计车速和齿轮位置的集成技术
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-09-10 DOI: 10.1109/ICDSP.2015.7251906
Hendrik Vincent Koops, F. Franchetti
{"title":"An ensemble technique for estimating vehicle speed and gear position from acoustic data","authors":"Hendrik Vincent Koops, F. Franchetti","doi":"10.1109/ICDSP.2015.7251906","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7251906","url":null,"abstract":"This paper presents a machine learning system that is capable of predicting the speed and gear position of a moving vehicle from the sound it makes. While audio classification is widely used in other research areas such as music information retrieval and bioacoustics, its application to vehicle sounds is rare. Therefore, we investigate predicting the state of a vehicle using audio features in a classification task. We improve the classification results using correlation matrices, calculated from signals correlating with the audio. In an experiment, the sound of a moving vehicle is classified into discretized speed intervals and gear positions. The experiment shows that the system is capable of predicting the vehicle speed and gear position with near-perfect accuracy over 99%. These results show that this system could be a valuable addition to vehicle anomaly detection and safety systems.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"62 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131008598","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
A stochastic geometry based performance analysis framework for massive MIMO systems with data-assisted uplink detection scheme 基于随机几何的海量MIMO系统数据辅助上行检测方案性能分析框架
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-09-10 DOI: 10.1109/ICDSP.2015.7252058
Rui Wang, Yifan Chen, Qingfeng Zhang, Hai Wang
{"title":"A stochastic geometry based performance analysis framework for massive MIMO systems with data-assisted uplink detection scheme","authors":"Rui Wang, Yifan Chen, Qingfeng Zhang, Hai Wang","doi":"10.1109/ICDSP.2015.7252058","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7252058","url":null,"abstract":"It has been shown in the existing literature that the data symbols can assist the massive MIMO transmission by relieving the issue of pilot contamination. In order to further evaluate the performance gain from system point of view, a stochastic geometry based framework is established in this paper to analyze the distribution of signal-to-interference ratio in a massive MIMO cellular network with data-assisted uplink detection scheme. The closed-from expressions of the asymptotic performance bounds are thereby derived. It is shown by numerical simulation that the analytical bounds fit the real performance with high accuracy.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123371495","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
Salient region detection via low-level features and high-level priors 通过低级特征和高级先验进行显著区域检测
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-07-21 DOI: 10.1109/ICDSP.2015.7252022
Mingqiang Lin, Zonghai Chen
{"title":"Salient region detection via low-level features and high-level priors","authors":"Mingqiang Lin, Zonghai Chen","doi":"10.1109/ICDSP.2015.7252022","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7252022","url":null,"abstract":"Humans have the capability to quickly prioritize external visual stimuli and localize their most interest in a scene. However, computational modeling of this basic intelligent behavior still remains a challenge. In this paper, we formulate salient region detection as a binary labeling problem that separates salient region from the background. A Conditional Random Field is learned to effectively combine low-level features with high-level priors. We use a set of low-level features including local features and global features. We use the low level visual cues based on the convex hull to compute the high-level priors. Experimental results on the large benchmark database demonstrate the proposed method performs well when against six state-of-the-art methods in terms of precision and recall.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123067073","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
Virtual surgical system in reduction of maxillary fracture 虚拟外科系统在上颌骨折复位中的应用
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-07-21 DOI: 10.1109/ICDSP.2015.7252050
Jing Zhang, Danni Li, Qi Liu, Ling He, Yunzhi Huang, Peng Li
{"title":"Virtual surgical system in reduction of maxillary fracture","authors":"Jing Zhang, Danni Li, Qi Liu, Ling He, Yunzhi Huang, Peng Li","doi":"10.1109/ICDSP.2015.7252050","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7252050","url":null,"abstract":"Reduction of maxillary fracture is widely performed in cranial-maxillofacial surgeries, but it requires skilled and experienced surgeons. A virtual surgery system aiming on this kind of surgery is designed. CHAI 3D is used for rendering the haptic feedback. A multi-proxy algorithm is proposed to prevent the handle of operation tool stabbing into the virtual models and causing misjudgment. With the Geomagic haptic device, operators can manipulate one virtual model in the 3D virtual environment. This system can be used to train medical students or for preoperative planning of complicated surgeries.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"312 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124430009","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
An automatic bleeding detection technique in wireless capsule endoscopy from region of interest 无线胶囊内窥镜感兴趣区自动出血检测技术
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-07-21 DOI: 10.1109/ICDSP.2015.7252090
T. Ghosh, S. Fattah, S. Bashar, C. Shahnaz, K. Wahid, Weiping Zhu, M. Ahmad
{"title":"An automatic bleeding detection technique in wireless capsule endoscopy from region of interest","authors":"T. Ghosh, S. Fattah, S. Bashar, C. Shahnaz, K. Wahid, Weiping Zhu, M. Ahmad","doi":"10.1109/ICDSP.2015.7252090","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7252090","url":null,"abstract":"Wireless capsule endoscopy (WCE) is a painless operative video technology to detect small intestine diseases, such as bleeding. Instead of using the most common RGB (red, green, blue) color scheme, in this paper, YIQ (luminance-Y, chrominance-IQ: in phase-I and quadrature-Q) color scheme is used for analyzing WCE video frames, which corresponds better to human color response characteristics. Analyzing the behavior of each of the four YIQ spaces, first, a region of interest is determined depending on the Q value of the pixels and some morphological operations. Next, instead of considering three spaces of YIQ color model separately, a new composite space Y.I/Q is proposed to capture intrinsic information about the luminance and chrominance of images. Four statistical measures, namely mean, median, skewness and minima of the pixel values in composite space within the ROI are computed as features. It is exhibited that use of composite space lower computational complexity as well as offers noticeably better discrimination between bleeding and non-bleeding pixels. For the purpose of classification, support vector machine (SVM) classifier is employed. Satisfactory bleeding detection performance result is achieved in terms of accuracy, sensitivity and specificity from severe experimentation on several WCE videos which is collected from a publicly available database. Also it is observed that proposed method over performs with comparing some of the existing methods.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123101929","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: 15
On the security of the schur-based watermarking schemes 基于字符的水印方案的安全性研究
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-07-21 DOI: 10.1109/ICDSP.2015.7251862
Victor Pomponiu, D. Cavagnino, Marco Botta
{"title":"On the security of the schur-based watermarking schemes","authors":"Victor Pomponiu, D. Cavagnino, Marco Botta","doi":"10.1109/ICDSP.2015.7251862","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7251862","url":null,"abstract":"This paper presents a security analysis of robust watermarking methods based on Schur decomposition in a general scenario. The security is defined as the difficulty to remove the watermark and to estimate the secrets used in the embedding process, supposing that the adversary possesses several watermarked digital contents. The theoretical analysis and extensive experimental results carried out prove that these schemes fail to secure the digital contents against malicious attacks.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125214929","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
Single image super-resolution via adaptive dictionary pair learning for wireless capsule endoscopy image 基于自适应字典对学习的无线胶囊内窥镜图像单幅超分辨
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-07-21 DOI: 10.1109/ICDSP.2015.7251943
Yi Wang, Cheng-Tao Cai, Yuexian Zou
{"title":"Single image super-resolution via adaptive dictionary pair learning for wireless capsule endoscopy image","authors":"Yi Wang, Cheng-Tao Cai, Yuexian Zou","doi":"10.1109/ICDSP.2015.7251943","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7251943","url":null,"abstract":"Wireless capsule endoscopy (WCE) is an innovative solution for gastrointestinal disease detection. Limited by WCE hardware and cost of manufacture, WCE image resolution is commonly low, which creates problems for attention to image details and visual perception in medical diagnosis. Under the sparse representation framework, we propose an adaptive dictionary pair learning method to obtain more appropriate representation of each patch with more relevant atoms according to patch content. Specifically, the dictionary pair is learned from high-low resolution cluster patches based on sparse constraint of input patches. Careful examination of the WCE images show there exist unnatural block areas. In order to further improve performance, the autoregressive model is applied to enhance local structure. Intensive experiments have been conducted on WCE image dataset and natural image dataset, including comparison test between the state-of-art methods and ours, and the results validate the effectiveness of the proposed method both on visual perception effect and objective indices.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117138200","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
Lp norm spectral regression for feature extraction in outlier conditions Lp范数光谱回归在离群条件下的特征提取
2015 IEEE International Conference on Digital Signal Processing (DSP) Pub Date : 2015-07-21 DOI: 10.1109/ICDSP.2015.7251930
Weiwei Zhou, Peiyang Li, Xurui Wang, Fali Li, Huan Liu, Rui Zhang, Teng Ma, Tiejun Liu, Daqing Guo, D. Yao, Peng Xu
{"title":"Lp norm spectral regression for feature extraction in outlier conditions","authors":"Weiwei Zhou, Peiyang Li, Xurui Wang, Fali Li, Huan Liu, Rui Zhang, Teng Ma, Tiejun Liu, Daqing Guo, D. Yao, Peng Xu","doi":"10.1109/ICDSP.2015.7251930","DOIUrl":"https://doi.org/10.1109/ICDSP.2015.7251930","url":null,"abstract":"Spectral regression is a newly proposed method which is widely used in signal processing and feature extraction. However, like most methods based on regression analysis, it is prone to outlier artifacts with large norm. In this paper, a novel regression function for SR is constructed in the Lp (p ≤ 1) norm space with the aim at compressing the outlier effects on pattern recognition. The quantitative evaluation using simulated outliers demonstrates the proposed method can effectively deal with the outliers introduced in the features.","PeriodicalId":216293,"journal":{"name":"2015 IEEE International Conference on Digital Signal Processing (DSP)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117146752","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
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