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Semantic Visual Features in Content-based Video Retrieval

Mu, Xiangming (2006) Semantic Visual Features in Content-based Video Retrieval. [Conference Paper]

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Abstract(s)

A new semantic visual features (e.g., car, mountain, and fire) navigation technology is proposed to improve the effectiveness of video retrieval. Traditional temporal neighbor browsing technology allows users to navigate temporal neighbors of a selected sample frame to find additional matches, while semantic visual feature browsing enables users to navigate keyframes that have similar features to the selected sample frame. A pilot evaluation was conducted to compare the effectiveness of three video retrieval designs that support 1) temporal neighbor browsing; 2) semantic visual feature browsing; and 3) fused browsing which is a combination of both temporal neighbor and semantic visual feature browsing. Two types of searching tasks: visual centric and non-visual centric tasks were applied. Initial results indicated that the semantic visual feature browsing system was more efficient for non-visual centric tasks.


Item Type:Conference Paper
Keywords:digital videos ; digital multimedia ; resource discovery ; information access ; search effectiveness
Subjects:I. Information treatment for information services > IB. Content analysis (A and I, class.)
B. Information use and sociology of information. > BH. Information needs and information requirements analysis.
H. Information sources, supports, channels. > HH. Audio-visual, Multimedia.
I. Information treatment for information services > IA. Cataloging, bibliographic control.
Full Metadata:Show all fields
ID Code:8482
Deposited By:Medeiros, Norm
Deposited On:15 Jan 2007
Last Modified:19 Nov 2008 12:54
Statistics:View statistics for this eprint

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