2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)最新文献_第8页

Single-pass distortion-smoothing encoding for low bit-rate video streaming applications 低比特率视频流应用的单次失真平滑编码

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1221597

Tao Chen, Zhihai He

引用次数: 5

Unsupervised object-based sprite coding system for tennis sport 网球运动的无监督对象精灵编码系统

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1220923

Ching-Yeh Chen, Shao-Yi Chien, Yi-Hau Chen, Yu-Wen Huang, Liang-Gee Chen

引用次数: 3

Speech-assisted facial expression analysis and synthesis for virtual conferencing systems 虚拟会议系统的语音辅助面部表情分析与合成

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1221365

Yao-Jen Chang, C. Hsieh, Pei-Wei Hsu, Yung-Chang Chen

引用次数: 5

Joint resolution enhancement and artifact reduction for MPEG-2 encoded digital video MPEG-2编码数字视频的联合分辨率增强和伪影减少

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1221601

Yibin Yang, L. Böröczky

引用次数: 1

Multi-resolution image inpainting 多分辨率图像绘制

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1220960

T. Shih, Liang-Chen Lu, Ying-Hong Wang, Rong-Chi Chang

引用次数: 27

Non-parametric approach to ICA using kernel density estimation 基于核密度估计的非参数ICA方法

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1221026

K. Sengupta, P. Burman

{"title":"Non-parametric approach to ICA using kernel density estimation","authors":"K. Sengupta, P. Burman","doi":"10.1109/ICME.2003.1221026","DOIUrl":"https://doi.org/10.1109/ICME.2003.1221026","url":null,"abstract":"Independent component analysis (ICA) has found a wide range of applications in signal processing and multimedia, ranging from speech cleaning to face recognition. This paper presents a non-parametric approach to the ICA problem that is robust towards outlier effects. The algorithm, for the first time in the field of ICA, adopts an intuitive and direct approach, focusing on the very definition of independence itself; i.e. the joint probability density function (pdf) of independent sources is factorial over the marginal distributions. This is contrary to traditional independent component analysis (ICA) algorithms, which achieve the objective by attempting to fulfill necessary conditions (but not sufficient) for independence. For example, the Jade algorithm attempts to approximate independence by minimizing higher order statistics. In the proposed algorithm, kernel density estimation is employed to provide a good approximation of the distributions that are required to be estimated. This estimation technique is inherently robust towards outlier effects. The application of kernel density estimation also enables the algorithm to be free from the assumptions of source distributions. Experimental results show that the algorithm is able to perform separation of sources in the presence of outliers, whereas existing algorithms like Jade and Info max break down under such conditions. The results have also shown that the proposed non-parametric approach is generally source distribution independent. In addition, it is able to separate non-Gaussian zero-kurtotic signals unlike the traditional ICA algorithms like Jade and Infomax.","PeriodicalId":118560,"journal":{"name":"2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)","volume":"82 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132153637","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

A paper-based interface for video browsing and retrieval 基于纸张的视频浏览和检索界面

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1221725

J. Graham, J. Hull

引用次数: 18

Visual attention based image browsing on mobile devices

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1220852

X. Fan, Xing Xie, Wei-Ying Ma, HongJiang Zhang, He-Qin Zhou

引用次数: 66

Embedded multiple description scalar quantizers for progressive image transmission 嵌入式多描述标量量化渐进图像传输

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1220970

A. Gavrilescu, A. Munteanu, P. Schelkens, J. Cornelis

引用次数: 14

Active selection for multi-example querying by content 根据内容进行多示例查询的主动选择

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) Pub Date : 2003-07-06 DOI: 10.1109/ICME.2003.1220950

A. Natsev, John R. Smith

{"title":"Active selection for multi-example querying by content","authors":"A. Natsev, John R. Smith","doi":"10.1109/ICME.2003.1220950","DOIUrl":"https://doi.org/10.1109/ICME.2003.1220950","url":null,"abstract":"Multi-example content-based retrieval (MECBR) is the process of querying content by specifying multiple query examples with single query iteration. MECBR attempts to mitigate some of the semantic limitations of traditional relevance feedback or CBR techniques by allowing multiple query examples and thus a more accurate modeling of the user's query need. It also attempts to minimize the burden on the user, as compared to relevance feedback methods, by eliminating the need for user feedback and limiting all interaction into a single query specification step. Multi-example content-based retrieval is therefore a simple alternative for modeling low- and mid-level semantics without the need for heavy user interaction or extensive training, as in interactive feedback systems or complex statistical modeling approaches. In this paper, we describe the MECBR technique in some detail and study methods for active selection of query examples and query features. In particular, we propose and investigate techniques for automatic query example selection, feature selection, and feature fusion. We compare different approaches and evaluate performance of different parameter settings through an extensive empirical study. We also compare MECBR performance to that of explicitly built semantic models using state-of-the-art support vector machines (SVM). We find that lightweight MECBR performs up to 60% better for rare concepts and only 12% to 25% worse for frequent concepts, as compared to heavy-weight SVM modeling! This shows that MECBR is not only a viable lightweight alternative to statistical semantic modeling but is also preferred for very diverse or rare-class semantic modeling situations.","PeriodicalId":118560,"journal":{"name":"2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121283725","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: 11