2011 IEEE International Symposium on Multimedia最新文献

Food Product Information Supplement System - Corresponding to Consumer Needs for Shopping and Eating Out 食品信息补充系统-与消费者购物和外出就餐需求相对应

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.72

Kayo H. Iizuka, Takuya Okawada, Yasuki Iizuka

引用次数: 2

Support Vector Regression Based Video Quality Prediction 基于支持向量回归的视频质量预测

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.84

Beibei Wang, D. Zou, Ran Ding

引用次数: 7

3D Face Fitting Method Based on 2D Active Appearance Models 基于二维活动外观模型的三维人脸拟合方法

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.11

Myung-Ho Ju, Hang-Bong Kang

引用次数: 2

Enhancing Local Binary Patterns Distinctiveness for Face Representation 增强局部二值模式特征的人脸表征

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.78

M. Ghahramani, W. Yau, E. Teoh

引用次数: 4

An Approach for Modeling the Effects of Video Resolution and Size on the Perceived Visual Quality 视频分辨率和尺寸对感知视觉质量影响的建模方法

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.82

Benjamin Belmudez, S. Möller

引用次数: 19

The Mosaic Camera: Streaming, Coding and Compositing Experiments 马赛克相机:流，编码和合成实验

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.106

Mashhour Solh, G. Al-Regib

引用次数: 0

Concept Learning with Co-occurrence Network for Image Retrieval 基于共现网络的概念学习图像检索

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.77

Linan Feng, B. Bhanu

{"title":"Concept Learning with Co-occurrence Network for Image Retrieval","authors":"Linan Feng, B. Bhanu","doi":"10.1109/ISM.2011.77","DOIUrl":"https://doi.org/10.1109/ISM.2011.77","url":null,"abstract":"This paper addresses the problem of concept learning for semantic image retrieval. Two types of semantic concepts are introduced in our system: the individual concept and the scene concept. The individual concepts are explicitly provided in a vocabulary of semantic words, which are the labels or annotations in an image database. Scene concepts are higher level concepts which are defined as potential patterns of co occurrence of individual concepts. Scene concepts exist since some of the individual concepts co-occur frequently across different images. This is similar to human learning where understanding of simpler ideas is generally useful prior to developing more sophisticated ones. Scene concepts can have more discriminative power compared to individual concepts but methods are needed to find them. A novel method for deriving scene concepts is presented. It is based on a weighted concept co-occurrence network (graph) with detected community structure property. An image similarity comparison and retrieval framework is described with the proposed individual and scene concept signature as the image semantic descriptors. Extensive experiments are conducted on a publicly available dataset to demonstrate the effectiveness of our concept learning and semantic image retrieval framework.","PeriodicalId":339410,"journal":{"name":"2011 IEEE International Symposium on Multimedia","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115829278","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

On the Applicability of Speaker Diarization to Audio Concept Detection for Multimedia Retrieval 基于多媒体检索的说话人特征化在音频概念检测中的应用

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.79

R. Mertens, Po-Sen Huang, L. Gottlieb, G. Friedland, Ajay Divakaran

{"title":"On the Applicability of Speaker Diarization to Audio Concept Detection for Multimedia Retrieval","authors":"R. Mertens, Po-Sen Huang, L. Gottlieb, G. Friedland, Ajay Divakaran","doi":"10.1109/ISM.2011.79","DOIUrl":"https://doi.org/10.1109/ISM.2011.79","url":null,"abstract":"Recently, audio concepts emerged as a useful building block in multimodal video retrieval systems. Information like \"this file contains laughter\", \"this file contains engine sounds\" or \"this file contains slow music\" can significantly improve purely visual based retrieval. The weak point of current approaches to audio concept detection is that they heavily rely on human annotators. In most approaches, audio material is manually inspected to identify relevant concepts. Then instances that contain examples of relevant concepts are selected -- again manually -- and used to train concept detectors. This approach comes with two major disadvantages: (1) it leads to rather abstract audio concepts that hardly cover the audio domain at hand and (2) the way human annotators identify audio concepts likely differs from the way a computer algorithm clusters audio data -- introducing additional noise in training data. This paper explores whether unsupervized audio segementation systems can be used to identify useful audio concepts by analyzing training data automatically and whether these audio concepts can be used for multimedia document classification and retrieval. A modified version of the ICSI (International Computer Science Institute) speaker diarization system finds segments in an audio track that have similar perceptual properties and groups these segments. This article provides an in-depth analysis on the statistic properties of similar acoustic segments identified by the diarization system in a predefined document set and the theoretical fitness of this approach to discern one document class from another.","PeriodicalId":339410,"journal":{"name":"2011 IEEE International Symposium on Multimedia","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131597263","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

Quantification of YouTube QoE via Crowdsourcing 通过众包量化YouTube QoE

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.87

T. Hossfeld, Michael Seufert, Matthias Hirth, T. Zinner, P. Tran-Gia, R. Schatz

引用次数: 362

Audio Recurrence Contribution to a Video-based TV Program Structuring Approach 音频递归对基于视频的电视节目结构方法的贡献

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-05 DOI: 10.1109/ISM.2011.15

Alina Elma Abduraman, Sid-Ahmed Berrani, B. Mérialdo

引用次数: 1