2010 IEEE International Conference on Imaging Systems and Techniques 2010
DOI: 10.1109/ist.2010.5548478
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Enabling distributed summarization of wireless capsule endoscopy video

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Cited by 10 publications
(3 citation statements)
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“…First, the gastroscopic video contents are diverse, and there is much redundant information, which confirms the necessity to obtain a quick idea of what happens in the video. Then, when the prolonged video, e.g., WCE, needs to be segmented into shots for processing [45,43], the gastroscopic video is long enough in terms of the information. Finally, the gastroscopic video contents are uncontrollable, although the video is obtained under the supervision of clinicians, which is similar to the video summarization of sports/news videos recorded by photographers [46][47][48].…”
Section: Related Workmentioning
confidence: 99%
“…First, the gastroscopic video contents are diverse, and there is much redundant information, which confirms the necessity to obtain a quick idea of what happens in the video. Then, when the prolonged video, e.g., WCE, needs to be segmented into shots for processing [45,43], the gastroscopic video is long enough in terms of the information. Finally, the gastroscopic video contents are uncontrollable, although the video is obtained under the supervision of clinicians, which is similar to the video summarization of sports/news videos recorded by photographers [46][47][48].…”
Section: Related Workmentioning
confidence: 99%
“…Although systems that divide the data among computational nodes, like the one presented in [6], or analyze only a subset of video frames can increase the throughput, the latency value is still going to be too high if the algorithm analyzing a single frame proves to be too slow. Also, in a continuous processing of a video stream analyzing only selected frames would not be desirable.…”
Section: Introductionmentioning
confidence: 99%
“…Η διαδικασία αυτή έχει ως αποτέλεσμα την εξαγωγή μιας σύνοψης του video που περιέχει μόνο τις εικόνες ενδιαφέροντος. Η πλειοψηφία των μεθοδολογιών περίληψης video χρησιμοποιούν χαμηλού επιπέδου χαρακτηριστικά χρώματος, υφής και σχήματος (Zhao & Meng, 2011;Fu et al, 2012;Lee et al, 2013;Zhao et al, 2015) για την ποσοτικοποίηση της ομοιότητας μεταξύ γειτονικών καρέ, ενώ άλλες προσεγγίσεις βασίζονται σε παραγοντοποίηση μη αρνητικών πινάκων με τεχνικές μηχανικής μάθησης με ή χωρίς επιτήρηση (Tsevas et al, 2008;Chu et al, 2010;Iakovidis et al, 2010;Ioannis et al 2010), ανάπτυξη πιθανοτικών μοντέλων ομοιότητας οπτικών και χωρικών περιγραφέων (Ismail et al, 2013) και στο μοντέλο παραμορφώσιμων δακτυλίων (model of deformable rings) (Szczypinski et al, 2009). Αντίστοιχα, οι τεχνικές ελέγχου της ταχύτητας αναπαραγωγής του video (Yagi et al, 2007;Vu et al, 2009a) προσαρμόζουν την ταχύτητα απεικόνισης των εικόνων με βάση το οπτικό τους περιεχόμενο.…”
Section: περίληψη Video και προσαρμοσμένη ταχύτητα αναπαραγωγήςunclassified