Image and Video Retrieval: 4th International Conference, CIVR 2005, Singapore, July 20-22, 2005, Proceedings
Wee-Kheng Leow, Michael S. Lew, Tat-Seng Chua, Wei-Ying Ma, Lekha Chaisorn, Erwin M. Bakker
Springer Science & Business Media, 2005 M07 14 - 674 pages
It was our great pleasure to host the 4th International Conference on Image and Video Retrieval (CIVR) at the National University of Singapore on 20–22 July 2005. CIVR aims to provide an international forum for the discussion of research challenges and exchange of ideas among researchers and practitioners in image/video retrieval technologies. It addresses innovative research in the broad ?eld of image and video retrieval. A unique feature of this conference is the high level of participation by researchers from both academia and industry. Another unique feature of CIVR this year was in its format – it o?ered both the traditional oral presentation sessions, as well as the short presentation cum poster sessions. The latter provided an informal alternative forum for animated discussions and exchanges of ideas among the participants. We are pleased to note that interest in CIVR has grown over the years. The number of submissions has steadily increased from 82 in 2002, to 119 in 2003, and 125 in 2004. This year, we received 128 submissions from the international communities:with81(63.3%)fromAsiaandAustralia,25(19.5%)fromEurope, and 22 (17.2%) from North America. After a rigorous review process, 20 papers were accepted for oral presentations, and 42 papers were accepted for poster presentations. In addition to the accepted submitted papers, the program also included 4 invited papers, 1 keynote industrial paper, and 4 invited industrial papers. Altogether, we o?ered a diverse and interesting program, addressing the current interests and future trends in this area.
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AdaBoost algorithm analysis annotation applied approach audio automatic average Berlin Heidelberg 2005 boundaries camera CBIR CIVR classiﬁcation classifier clips cluster color color histogram Computer Vision concepts Conf conﬁguration content-based image retrieval correlogram corresponding dataset deﬁned descriptors diﬀerent distance distribution document domain eﬀective eﬃcient evaluation example experiments extracted face detections feature extraction feature vectors ﬁeld ﬁle ﬁnd ﬁrst fractal frames function Gabor graph histogram IEEE Image and Video indexing information retrieval interactive kernel key frame keywords label learning Leow LNCS machine learning matching matrix Multimedia object movie ontology paper parameters pixels precision Proc query rank recognition region relevance feedback represent representation retrieval performance selected semantic semantic gap sequence shape shows signiﬁcant similarity measure spatial speciﬁc story segmentation Support Vector Machines techniques texture topics trajectories TRECVID video retrieval visual features