2009 IEEE 17th Signal Processing and Communications Applications Conference最新文献_第9页

Automated clustering of large data sets based on a topology representing graph 基于拓扑表示图的大型数据集的自动聚类

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136521

K. Tasdemir

引用次数: 0

Channel output error (COE) for channel order estimation 通道顺序估计的通道输出错误(COE)

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136331

S. Karakutuk, T. E. Tuncer

引用次数: 0

Cell nuclei segmentation in pap smear test images 巴氏涂片检查图像中的细胞核分割

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136479

Asi Kale, S. Aksoy, S. Onder

引用次数: 4

Object segmentation in multi-view video via color, depth and motion cues 通过颜色，深度和运动线索在多视点视频中的对象分割

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136484

C. Çigla, Aydin Alatan

{"title":"Object segmentation in multi-view video via color, depth and motion cues","authors":"C. Çigla, Aydin Alatan","doi":"10.1109/SIU.2009.5136484","DOIUrl":"https://doi.org/10.1109/SIU.2009.5136484","url":null,"abstract":"In the light of dense depth map estimation, motion estimation and object segmentation, the research on multi-view video (MVV) content has becoming increasingly popular due to its wide application areas in the near future. In this work, object segmentation problem is studied by additional cues due to depth and motion fields. Segmentation is achieved by modeling images as graphical models and performing popular Normalized Cuts method with some modifications. In the graphical models, each node is represented by a group of pixels, instead of individual pixels, which are obtained as a result of over-segmentation of the images. These over-segmented regions are also utilized in the dense depth map estimation step; in which 3D planar models are assigned for each of these sub-regions. Moreover, optical flow is estimated based on affine motion assumption for these regions. The links of the graphical models are weighted according to the depth, motion and color similarities of the pixel groups due to these regions. Once the links are obtained, segmentation is achieved by recursively bi-partitioning the graph via removing the weak links. Experiments indicate that the proposed framework achieves precise segmentation results for MVV sequences.","PeriodicalId":219938,"journal":{"name":"2009 IEEE 17th Signal Processing and Communications Applications Conference","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121557011","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

Automatic emotion recognition for facial expression animation from speech 语音面部表情动画的自动情感识别

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136564

E. Bozkurt, E. Erzin, Ç. Erdem, A. Erdem

{"title":"Automatic emotion recognition for facial expression animation from speech","authors":"E. Bozkurt, E. Erzin, Ç. Erdem, A. Erdem","doi":"10.1109/SIU.2009.5136564","DOIUrl":"https://doi.org/10.1109/SIU.2009.5136564","url":null,"abstract":"We present a framework for automatically generating the facial expression animation of 3D talking heads using only the speech information. Our system is trained on the Berlin emotional speech dataset that is in German and includes seven emotions. We first parameterize the speech signal with prosody related features and spectral features. Then, we investigate two different classifier architectures for the emotion recognition: Gaussian mixture model (GMM) and hidden Markov model (HMM) based classifiers. In the experimental studies, we achieve an average emotion recognition rate of 83.42% using 5-fold stratified cross validation (SCV) method with a GMM classifier based on Mel frequency cepstral coefficients (MFCC) and dynamic MFCC features. Moreover, decision fusion of two GMM classifiers based on MFCC and line spectral frequency (LSF) features yields an average recognition rate of 85.30%. Also, a second-stage decision fusion of this result with a prosody-based HMM classifier further advances the average recognition rate up to 86.45%. Experimental results on automatic emotion recognition to drive facial expression animation synthesis are encouraging.","PeriodicalId":219938,"journal":{"name":"2009 IEEE 17th Signal Processing and Communications Applications Conference","volume":"246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131828379","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

Blind channel equalization of multiple-input/single-output FIR systems for chaotic digital communication systems 混沌数字通信系统中多输入单输出FIR系统的盲信道均衡

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136423

G. Çetinel, C. Vural

引用次数: 0

Joint network-channel coding with Repeat Accumulate codes for wireless relay networks 无线中继网络中具有重复累加码的联合网络信道编码

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136368

O. Ozdemir, A. O. Yılmaz

引用次数: 0

CA-CFAR detection in spatially correlated K-distributed sea clutter 空间相关k分布海杂波的CA-CFAR检测

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136527

Aysin Cetin Hamurcu, A. Hizal

引用次数: 1

Effect of filtering on processing of thermal lens fringes by single sideband modulation technique 滤波对单边带调制技术处理热透镜条纹的影响

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136321

A. Emir, Z. Saraç

引用次数: 0

Linear separability analysis for stacked generalization architecture 叠式泛化结构的线性可分性分析

2009 IEEE 17th Signal Processing and Communications Applications Conference Pub Date : 2009-04-09 DOI: 10.1109/SIU.2009.5136569

M. Ozay, Fatoş T. Yarman Vural

引用次数: 0