K
Klaus Schöffmann
Researcher at Alpen-Adria-Universität Klagenfurt
Publications - 20
Citations - 441
Klaus Schöffmann is an academic researcher from Alpen-Adria-Universität Klagenfurt. The author has contributed to research in topics: Automatic summarization & Video tracking. The author has an hindex of 8, co-authored 20 publications receiving 380 citations. Previous affiliations of Klaus Schöffmann include Information Technology University.
Papers
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Journal ArticleDOI
Learning laparoscopic video shot classification for gynecological surgery
TL;DR: The main conclusion of this work is that advances in general image classification methods transfer to the domain of endoscopic surgery videos in gynecology, relevant as this domain is different from natural images, e.g. it is distinguished by smoke, reflections, or a limited amount of colors.
Journal ArticleDOI
Interactive Search or Sequential Browsing? A Detailed Analysis of the Video Browser Showdown 2018
Jakub Lokoč,Gregor Kovalčík,Bernd Münzer,Klaus Schöffmann,Werner Bailer,Ralph Gasser,Stefanos Vrochidis,Phuong Anh Nguyen,Sitapa Rujikietgumjorn,Kai Uwe Barthel +9 more
TL;DR: The results collected at the VBS evaluation server confirm that searching for one particular scene in the collection when given a limited time is still a challenging task for many of the approaches, and reveal that user-centric interfaces are still required to mediate access to specific content.
Proceedings ArticleDOI
Introduction to the Fourth Annual Lifelog Search Challenge, LSC'21
Cathal Gurrin,Björn Þór Jónsson,Klaus Schöffmann,Duc-Tien Dang-Nguyen,Jakub Lokoč,Minh-Triet Tran,Wolfgang Hürst,Luca Rossetto,Graham Healy +8 more
TL;DR: An overview of the challenge motivates the challenge, the dataset and system configuration used in the challenge are presented, and the participating teams are presented.
Journal ArticleDOI
A novel tool for summarization of arthroscopic videos
TL;DR: This paper presents a video summarization tool and demonstrates how it can be successfully used in the domain of arthroscopic videos, taking advantage of several domain-specific aspects without losing its ability to work on general-purpose videos.
Book ChapterDOI
An evaluation of parallelization concepts for baseline-profile compliant H.264/AVC decoders
TL;DR: This work proposes and evaluates different ways of using multithreading to speed-up the authors' .NET implemented decoder, and finds functional partitioning and macroblock pipelining prove to be a good alternative for almost all evaluated videos.