Shih-Fu Chang, William Chen, Hari Sundaram  Home/Search
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Abstract: The rapid growth of visual data over the last few years has lead to many schemes for retrieving such data. With content-based systems today, there exists a significant gap between the user's information needs and what the systems can deliver. We propose to bridge this gap, by introducing the novel idea of Semantic Visual Templates (SVT). Each template represents a personalized view of concepts (e.g. slalom, meetings, sunsets etc.), The SVT is represented using a set of successful queries, which ... (Update)
Context of citations to this paper: More
.... image components to train a neural network is presented in [5] The concept of the semantic visual template is introduced by Chang et al. [6]. The user is asked to identify a possible range of color, texture, shape or motion parameters to express his or her query, which is then...
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CBSA: Content-based Soft Annotation for Multimodal Image.. - Chang, Goh, Sychay, Wu (2003) (Correct)
Confidence-based Dynamic Ensemble for Image Annotation and.. - Li, Goh, Chang (2003) (Correct)
Language-based Querying of Image Collections on the Basis of.. - Town, Sinclair (2004) (Correct)
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0.6: A Fully Automated Content Based Video Search.. - Chang, Chen.. (1997) (Correct)
0.5: A Knowledge Engineering Approach For Image Classification Based .. - Paek, Chang (2000) (Correct)
0.5: Storage and Management of Similar Images - Jomier, Manouvrier, Rukoz (2000) (Correct)
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0.4: Motion Trajectory Matching of Video Objects - Chen, Chang (Correct)
0.2: VideoQ: A Fully Automated Video Retrieval System Using Motion.. - Chang (1998) (Correct)
0.2: Efficient Video Sequence Retrieval in Large Repositories - Hari Sundaram And (1999) (Correct)
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4: Visual Information Retrieval from Large Distributed Online Repositories - Chang, Smith et al. - 1997
4: Multi-stage classification of images from features and related text - Smith, Chang - 1997
4: Context and Configuration Based Scene Classification (context) - Lipson - 1996
BibTeX entry: (Update)
S.F. Chang, W. Chen, H. Sundaram, Semantic Visual Templates: Linking Visual Features to Semantics, to appear in ICIP '98, Workshop on Content Based Video Search and Retrieval, Chicago IL, Oct. 1998. http://citeseer.ist.psu.edu/chang98semantic.html More
@inproceedings{ changsemantic,
author = "S. Chang and W. Chen and H. Sundaram",
title = "Semantic Visual Templates: Linking Visual Features to Semantics",
pages = "531--535",
url = "citeseer.ist.psu.edu/chang98semantic.html" }
Citations (may not include all citations):283 Efficient and Effective Querying by Image Content - Faloutsos, Flickner et al. - 1993
3 Pala Visual Image Retrieval by Elastic Matching of User Sket.. (context) - Bimbo - 1997
3 Virage Video Engine SPIE Proceedings on Storage and Retrieva.. (context) - Hamrapur, Gupta et al. - 1997
2 Zhang On Image Classification: City vs (context) - Vailaya, Jain - 1998
2 Chang VisualSEEK: A Fully Automated Content-Based Image Quer.. (context) - Smith - 1996
1 Zhong VideoQ: An Automated Content Based Video Search System.. (context) - Chang, Chen et al. - 1997
1 Yianilos Target Testing and the PicHunter Bayesian Multimedi.. (context) - Cox, Miller et al. - 1996
The graph only includes citing articles where the year of publication is known.
Documents on the same site (http://www.ctr.columbia.edu/~sundaram/research.html): More
VideoQ: An Automated Content Based Video Search.. - Chang, Chen.. (1997) (Correct)
VideoQ: A Fully Automated Video Retrieval System Using Motion.. - Chang (1998) (Correct)
A Fully Automated Content Based Video Search.. - Chang, Chen.. (1997) (Correct)
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