On usage models of content-based image search, filtering, and annotation

被引：1

作者：

Telleen-Lawton, David ^{[1
]}

Chang, Edward Y. ^{[1
]}

Cheng, Kwang-Ting ^{[1
]}

Chang, Cheng-Wei B. ^{[1
]}

机构：

[1] VIMA Technol, Santa Barbara, CA USA

来源：

INTERNET IMAGING VII | 2006年 / 6061卷

关键词：

content-based image retrieval; active learning; information filtering; usage models; CBIR;

D O I：

10.1117/12.655792

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

VIMA has experienced an increasing demand for Content-based Image Retrieval (CBIR) systems since late 2004. In this paper. we report the search. filtering. and annotation systems that we have developed and deployed. and the user models of these systems. The objective of this paper is to provide to the researchers and developers in the area of image retrieval, guidelines for measuring the performance of their algorithms/systems, in a way that is consonant with the requirements of the users. We also enumerate technical challenges of building CBIR systems. and Outline our Solutions to tackle these challenges.

引用

页数：12

共 12 条

[1] CBSA: Content-based soft annotation for multimodal image retrieval using Bayes point machines [J].

Chang, E ;

Goh, K ;

Sychay, G ;

Wu, G .

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2003, 13 (01) :26-38

[2]

CHANG E, 2005, ACM SIGMOD CVDB WORK

[3]

Chang EY, 2003, 2003 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL 3, PROCEEDINGS, P609

[4]

CHANG EY, 2006, DIGITAL MULTIMEDIA P

[5]

CHANG EY, 1998, IS T SPIE S VOIC VID

[6]

DESHPANDE A, 2004, IEEE CVPR

[7]

Goh K.-S., 2004, P 12 ANN ACM INT C M, P564, DOI DOI 10.1145/1027527.1027664

[8]

NAAMAN M, 2003, INT C COOP INF SYST

[9] Enhanced perceptual distance functions and indexing for image replica recognition [J].

Qamra, A ;

Meng, Y ;

Chang, EY .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2005, 27 (03) :379-391

[10]

Tong S., 2001, P 9 ACM INT C MULTIM, P107, DOI [10.1145/500141.500159, DOI 10.1145/500141.500159]

← 1 2 →