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TREC
2001
13 years 8 months ago
Integrating Features, Models, and Semantics for TREC Video Retrieval
In this paper, we describe a system for automatic and interactive content-based retrieval of video that integrates features, models, and semantics. The novelty of the approach lie...
John R. Smith, Savitha Srinivasan, Arnon Amir, San...
ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
14 years 28 days ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
ICIP
2001
IEEE
14 years 9 months ago
VISMap: an interactive image/video retrieval system using visualization and concept maps
Images and videos can be indexed by multiple features at different levels, such as color, texture, motion, and text annotation. Organizing this information into a system so that u...
William Chen, Shih-Fu Chang
ICCV
2007
IEEE
14 years 1 months ago
Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval
Given a query image of an object, our objective is to retrieve all instances of that object in a large (1M+) image database. We adopt the bag-of-visual-words architecture which ha...
Ondrej Chum, James Philbin, Josef Sivic, Michael I...
TKDE
2008
195views more  TKDE 2008»
13 years 7 months ago
Learning a Maximum Margin Subspace for Image Retrieval
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
Xiaofei He, Deng Cai, Jiawei Han