2006 IEEE 14th Signal Processing and Communications Applications最新文献_第4页

Automatic Video Text Localization and Recognition 自动视频文本定位和识别

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659917

A. Saracoglu, A. Alatan

引用次数: 16

Gabor Factor Analysis for 2D+3D Facial Landmark Localization 二维+三维面部地标定位的Gabor因子分析

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659894

A. Salah

引用次数: 8

Design of Hybrid Fiber Raman and EDFAs Operated by Optimal Performance 性能最优的混合光纤拉曼和edfa设计

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659897

C. Berkdemir, S. Ozsoy

引用次数: 0

A Tool for Creating Calibrated Images 创建校准图像的工具

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659836

U. Yilmaz, O. Hellwich

引用次数: 2

Language Modelling Approaches for Turkish Large Vocabulary Continuous Speech Recognition Based on Lattice Rescoring 基于点阵评分的土耳其语大词汇连续语音识别语言建模方法

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659773

E. Arisoy, M. Saraçlar

{"title":"Language Modelling Approaches for Turkish Large Vocabulary Continuous Speech Recognition Based on Lattice Rescoring","authors":"E. Arisoy, M. Saraçlar","doi":"10.1109/SIU.2006.1659773","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659773","url":null,"abstract":"In this paper, we have tried some language modelling approaches for large vocabulary continuous speech recognition (LVCSR) of Turkish. The agglutinative nature of Turkish makes Turkish a challenging language in terms of speech recognition since it is impossible to include all possible words in the recognition lexicon. Therefore, instead of using words as recognition units, we use a data-driven sub-word approach called morphs. This method was previously applied to Finnish, Estonian and Turkish and promising recognition results were achieved compared to words as recognition units. In our database, we obtained word error rates (WER) of 38.8% for the baseline word-based model and 33.9% for the baseline morph-based model. In addition, we tried some new methods. Recognition lattice outputs of each model were rescored with the root-based and root-class-based models for the word-based case and first-morph-based model for the morph-based case. The word-root composition approach achieves a 0.5% increase in the recognition performance. However, other two approaches fail due to the non-robust estimates over the baseline models","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"81 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124018144","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

Three-Band Modeling Using Prominent Edges for Face Alignment 利用突出边缘进行人脸对齐的三波段建模

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659716

F. Kahraman, B. Kurt, M. Gokmen

{"title":"Three-Band Modeling Using Prominent Edges for Face Alignment","authors":"F. Kahraman, B. Kurt, M. Gokmen","doi":"10.1109/SIU.2006.1659716","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659716","url":null,"abstract":"Fundamental difficulty in face recognition systems is mainly related to successful human face alignment from the input image. In recent years, model based approaches get attention among others. Most powerful method among model-based approaches is known as active appearance model. The method accomplishes this by constructing a relation between shape and texture. Face alignment methods are required to work well even in the presence of illumination and affine transformation. Classical AAM extracts texture and shape information from the training image by using RGB color space. Classical AAM can only handle images having the same or similar color distribution to the images in the training set. Classical AAM cannot align images obtained under different lightning conditions from the training images even if the same person exists in the training database. In this study, we propose to use features which are shown to be less sensitive to illumination changes instead of directly using RGB colors. The proposed AAM is called three-band AAM. The bands are hue, hill, and luminance. Prominent edge detection constitutes the most important part of the model. Experimental studies show that prominent edges do not depend on illumination changes much when compared the original color space, and the three-band AAM based face alignment outperforms the classical AAM in terms of alignment precision","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124019824","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

Reduction of Sensory Inaccuracy in Nonlinear Systems using Particle Filters 用粒子滤波降低非线性系统的感觉误差

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659715

H. Bayram, A. Ertuzun, H. Bozma

引用次数: 0

Illumination Subspaces based Robust Face Recognition 基于光照子空间的鲁棒人脸识别

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659916

D. Kern, H. K. Ekenel, R. Stiefelhagen, Aydinlanmadan Kaynaklanan

引用次数: 0

Acoustic Echo Cancellation with Adaptive Filtering 自适应滤波声学回声消除

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659783

Yanki Iptali, Ahmet Refit, Kavsaoglu Yuksel Ozbay

引用次数: 2

Detection and Analysis of Quick Phase Eye Movements in Nystagmus (VNG) 眼球震颤(VNG)的快相眼动检测与分析

2006 IEEE 14th Signal Processing and Communications Applications Pub Date : 2006-04-17 DOI: 10.1109/SIU.2006.1659819

A. Aydemir, A. Uneri

引用次数: 8