MiAlbum - a system for home photo managemet using the semi-automatic image annotation approach
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
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ACM Computing Surveys (CSUR)
MyPhotos: a system for home photo management and processing
Proceedings of the tenth ACM international conference on Multimedia
AutoAlbum: Clustering Digital Photographs using Probabilistic Model Merging
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
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ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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ETP '03 Proceedings of the 2003 ACM SIGMM workshop on Experiential telepresence
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International Journal of Computer Vision
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ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
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CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
International Journal of Computer Vision
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MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Home photo retrieval: time matters
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
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CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Image classification for content-based indexing
IEEE Transactions on Image Processing
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Information Sciences: an International Journal
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In this paper, we propose a content-based method the for semi- automatic organization of photo albums based on the analysis of how different users organize their own pictures. The goal is to help the user in dividing his pictures into groups characterized by a similar semantic content. The method is semi-automatic: the user starts to assign labels to the pictures and unlabeled pictures are tagged with proposed labels. The user can accept the recommendation or make a correction. The method is conceptually articulated in two parts. First, we use a suitable feature representation of the images to model the different classes that the users have collected, second, we look for correspondences between the criteria used by the different users. A quantitative evaluation of the proposed approach is proposed based on pictures of a set of members of the flickr® photo-sharing community.