@InProceedings{BeecksEndoRetrieval2015, author = {Beecks, Christian and Schoeffmann, Klaus and Lux, Mathias and Uysal, Merih Seran and Seidl, Thomas}, booktitle = {Proceedings of the IEEE International Symposium on Multimedia 2015 (ISM 2015)}, title = {Endoscopic Video Retrieval: A Signature-based Approach for Linking Endoscopic Images with Video Segments}, year = {2015}, address = {Los Alamitos, CA}, editor = {Del Bimbo, Alberto and Chen, Shu-Ching and Wang, Haohong and Yu, Heather and Zimmermann, Roger}, month = {dec}, pages = {1-6}, publisher = {IEEE}, abstract = {In the field of medical endoscopy more and more surgeons are changing over to record and store videos of their endoscopic procedures, such as surgeries and examinations, in long-term video archives. In order to support surgeons in accessing these endoscopic video archives in a content-based way, we propose a simple yet effective signature-based approach: the Signature Matching Distance based on adaptive-binning feature signatures. The proposed distance-based similarity model facilitates an adaptive representation of the visual properties of endoscopic images and allows for matching these properties efficiently. We conduct an extensive performance analysis with respect to the task of linking specific endoscopic images with video segments and show the high efficacy of our approach. We are able to link more than 88% of the endoscopic images to their corresponding correct video segments, which improves the current state of the art by one order of magnitude.}, language = {EN}, location = {Miami, Florida, USA}, talkdate = {2015.12.14}, talktype = {registered} }