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» Using High-Level Semantic Features in Video Retrieval
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ICIP
2003
IEEE
15 years 11 months ago
Annotating retrieval database with active learning
In this paper, we describe a retrieval system that uses hidden annotation to improve the performance. The contribution of this paper is a novel active learning framework that can ...
Cha Zhang, Tsuhan Chen
ICITA
2005
IEEE
15 years 3 months ago
Combining Diversity-Based Active Learning with Discriminant Analysis in Image Retrieval
Small-sample learning in image retrieval is a pertinent and interesting problem. Relevance feedback is an active area of research that seeks to find algorithms that are robust wi...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
ICCV
2009
IEEE
14 years 7 months ago
Building recognition using sketch-based representations and spectral graph matching
In this work, we address the problem of building recognition across two camera views with large changes in scales and viewpoints. The main idea is to construct a semantically rich...
Yu-Chia Chung, Tony X. Han, Zhihai He
CVPR
2009
IEEE
16 years 4 months ago
Learning query-dependent prefilters for scalable image retrieval
We describe an algorithm for similar-image search which is designed to be efficient for extremely large collections of images. For each query, a small response set is selected by...
Lorenzo Torresani (Dartmouth College), Martin Szum...
ICMCS
2006
IEEE
150views Multimedia» more  ICMCS 2006»
15 years 3 months ago
Hierarchical Summarization of Videos by Tree-Structured Vector Quantization
Accurate grouping of video shots could lead to semantic indexing of video segments for content analysis and retrieval. This paper introduces a novel cluster analysis which, depend...
Sergio Benini, Aldo Bianchetti, Riccardo Leonardi,...