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» Unifying Keywords and Visual Contents in Image Retrieval
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CEE
2010
67views more  CEE 2010»
14 years 9 months ago
Series feature aggregation for content-based image retrieval
Feature aggregation is a critical technique in content-based image retrieval systems that employ multiple visual features to characterize image content. One problem in feature aggr...
Jun Zhang, Lei Ye
MM
2009
ACM
172views Multimedia» more  MM 2009»
15 years 4 months ago
Concept, content and the convict
This paper describes the concepts behind and implementation of the multimedia art work Alan01 / AlanOnline, which wakes up the 1952 criminally convicted Alan Turing as a piece of ...
Mika Luma Tuomola, Teemu Korpilahti, Jaakko Pesone...
ICMCS
2007
IEEE
167views Multimedia» more  ICMCS 2007»
14 years 9 months ago
A Probability Model for Image Annotation
Automatic image annotation is a promising solution to enable more effective image retrieval by keywords. Traditionally, statistical models for image auto-annotation predicate each...
Yong Ge, Richang Hong, Zhiwei Gu, Rong Zhang, Xiuq...
ICMCS
2010
IEEE
186views Multimedia» more  ICMCS 2010»
14 years 10 months ago
Worthy visual content on mobile through interactive video streaming
This paper builds on an interactive streaming architecture that supports both user feedback interpretation, and temporal juxtaposition of multiple video bitstreams in a single str...
Ivan Alen Fernandez, Christophe De Vleeschouwer, F...
ICDE
2006
IEEE
191views Database» more  ICDE 2006»
15 years 11 months ago
Query Decomposition: A Multiple Neighborhood Approach to Relevance Feedback Processing in Content-based Image Retrieval
Today's Content-Based Image Retrieval (CBIR) techniques are based on the "k-nearest neighbors" (kNN) model. They retrieve images from a single neighborhood using lo...
Kien A. Hua, Ning Yu, Danzhou Liu