2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI)最新文献

Efficient indexing structures for fast media search and browsing 高效的索引结构，用于快速媒体搜索和浏览

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972533

Marco Teixeira, João Magalhães

引用次数: 0

Spoken WordCloud: Clustering recurrent patterns in speech 口语词云:语音中重复模式的聚类

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972534

Rémi Flamary, Xavier Anguera Miró, Nuria Oliver

引用次数: 24

Unsupervised anchorpersons differentiation in news video 新闻视频中无监督主持人的分化

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972531

M. Broilo, A. Basso, F. D. Natale

引用次数: 8

Efficient video summarization and retrieval tools 高效的视频摘要和检索工具

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972518

Víctor Valdés, J. Sanchez

引用次数: 8

Using LIDO to handle 3D cultural heritage documentation data provenance 利用LIDO处理三维文物文献资料来源

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972517

D. Pitzalis, F. Niccolucci, M. Cord

引用次数: 3

Unsupervised scene detection in Olympic video using multi-modal chains 基于多模态链的奥运视频无监督场景检测

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972529

Gert-Jan Poulisse, Marie-Francine Moens

引用次数: 4

Interactive social, spatial and temporal querying for multimedia retrieval 多媒体检索的交互式社会、空间和时间查询

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972512

G. C. D. Silva, K. Aizawa, Yuki Arase, Xing Xie

引用次数: 2

Binary SIFT: Fast image retrieval using binary quantized SIFT features 二值SIFT:使用二值量化SIFT特征的快速图像检索

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972548

K. A. Peker

{"title":"Binary SIFT: Fast image retrieval using binary quantized SIFT features","authors":"K. A. Peker","doi":"10.1109/CBMI.2011.5972548","DOIUrl":"https://doi.org/10.1109/CBMI.2011.5972548","url":null,"abstract":"SIFT features are widely used in content based image retrieval. Typically, a few thousand keypoints are extracted from each image. Image matching involves distance computations across all pairs of SIFT feature vectors from both images, which is quite costly. We show that SIFT features perform surprisingly well even after quantizing each component to binary, when the medians are used as the quantization thresholds. Quantized features preserve both distinctiveness and matching properties. Almost all of the features in our 5.4 million feature test set map to distinct binary patterns after quantization. Furthermore, number of matches between images using both the original and the binary quantized SIFT features are quite similar. We investigate the distribution of SIFT features and observe that the space of 128-D binary vectors has sufficient capacity for the current performance of SIFT features. We use component median values as quantization thresholds and show through vector-to-vector distance comparisons and image-to-image matches that the resulting binary vectors perform comparable to original SIFT vectors. We also discuss computational and storage gains. Binary vector distance computation reduces to bit-wise operations. Square operation is eliminated. Fast and efficient indexing techniques such as the signatures used for chemical databases can also be considered.","PeriodicalId":358337,"journal":{"name":"2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131406192","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: 32

Semi-supervised object recognition using flickr images 使用flickr图像的半监督对象识别

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972550

E. Chatzilari, S. Nikolopoulos, S. Papadopoulos, Christos Zigkolis, Y. Kompatsiaris

引用次数: 15

ImmEx: IMMersive text documents exploration system ImmEx:沉浸式文本文档探索系统

2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI) Pub Date : 2011-06-13 DOI: 10.1109/CBMI.2011.5972511

Mario Cataldi, Luigi Di Caro, C. Schifanella

{"title":"ImmEx: IMMersive text documents exploration system","authors":"Mario Cataldi, Luigi Di Caro, C. Schifanella","doi":"10.1109/CBMI.2011.5972511","DOIUrl":"https://doi.org/10.1109/CBMI.2011.5972511","url":null,"abstract":"Common search engines, especially web-based, rely on standard keyword-based queries and matching algorithms using word frequencies, topics recentness, documents authority and/or thesauri. However, even if those systems present efficient retrieval algorithms, they are not able to lead the user into an intuitive exploration of large data collections because of their cumbersome presentations of the results (e.g. large lists of entries). Moreover, these methods do not provide any mechanism to retrieve other relevant information associated to those contents and, even if query refinement methods are proposed, it is really hard to express it because of the user's inexperience and common lack of familiarity with terminology. Therefore, we propose ImmEx, a novel visual navigational system for an immersive exploration of text documents that overcomes these problems by leveraging the intuitiveness of semantically-related images, retrieved in real-time from popular image sharing services. ImmEx lets independently explore large text collection through a novel approach that exploits the directness of the images and their user-generated metadata. We finally analyze the efficiency and usability of the proposed system by providing case and user studies.","PeriodicalId":358337,"journal":{"name":"2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116692795","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