TY - JOUR
T1 - Travelmedia
T2 - An intelligent management system for media captured in travel
AU - Chu, Wei Ta
AU - Li, Cheng Jung
AU - Tseng, Sheng Chun
N1 - Funding Information:
The authors would like to thank Chia-Hung Lin, Ya-Lin Lee, and Che-Cheng Lin for their efforts on preliminary results of this work. The authors would also like to thank anonymous reviewers for giving valuable comments. The work was partially supported by the National Science Council of Taiwan, Republic of China under research contract NSC 99-2221-E-194-036 and NSC 98-2221-E-194-056 .
PY - 2011/1
Y1 - 2011/1
N2 - A media management system exploiting characteristics of travel media is designed to facilitate efficient management and browsing. According to travel schedules, travel media often have implicit thematic structure. Correlation between different modalities also provides implicit cues to media analysis. In this system, we exploit techniques of near-duplicate detection to select representative photos, and determine region-of-interest in photos to enhance browsing experience. For face-name association, a face clustering module based on visual language models is constructed. To systematically segment travel videos of bad visual quality and significant motion, we explore correlation between photos and videos based on approximate visual word histogram matching. Experimental results demonstrate the effectiveness of the proposed approaches and show that they are practical functions.
AB - A media management system exploiting characteristics of travel media is designed to facilitate efficient management and browsing. According to travel schedules, travel media often have implicit thematic structure. Correlation between different modalities also provides implicit cues to media analysis. In this system, we exploit techniques of near-duplicate detection to select representative photos, and determine region-of-interest in photos to enhance browsing experience. For face-name association, a face clustering module based on visual language models is constructed. To systematically segment travel videos of bad visual quality and significant motion, we explore correlation between photos and videos based on approximate visual word histogram matching. Experimental results demonstrate the effectiveness of the proposed approaches and show that they are practical functions.
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U2 - 10.1016/j.jvcir.2010.10.008
DO - 10.1016/j.jvcir.2010.10.008
M3 - Article
AN - SCOPUS:78650732488
VL - 22
SP - 93
EP - 104
JO - Journal of Visual Communication and Image Representation
JF - Journal of Visual Communication and Image Representation
SN - 1047-3203
IS - 1
ER -