The Experts below are selected from a list of 54381 Experts worldwide ranked by ideXlab platform
Klaus Schoeffmann - One of the best experts on this subject based on the ideXlab platform.
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Interactive Video retrieval in the age of deep learning detailed evaluation of vbs 2019
IEEE Transactions on Multimedia, 2021Co-Authors: Luca Rossetto, Ralph Gasser, Jakub Lokoč, Werner Bailer, Klaus Schoeffmann, Bernd Muenzer, Tomáš Souček, Phuong Anh Nguyen, Paolo Bolettieri, Andreas LeibetsederAbstract:Despite the fact that automatic content analysis has made remarkable progress over the last decade – mainly due to significant advances in machine learning – Interactive Video retrieval is still a very challenging problem, with an increasing relevance in practical applications. The Video Browser Showdown (VBS) is an annual evaluation competition that pushes the limits of Interactive Video retrieval with state-of-the-art tools, tasks, data, and evaluation metrics. In this paper, we analyse the results and outcome of the 8th iteration of the VBS in detail. We first give an overview of the novel and considerably larger V3C1 dataset and the tasks that were performed during VBS 2019. We then go on to describe the search systems of the six international teams in terms of features and performance. And finally, we perform an in-depth analysis of the per-team success ratio and relate this to the search strategies that were applied, the most popular features, and problems that were experienced. A large part of this analysis was conducted based on logs that were collected during the competition itself. This analysis gives further insights into the typical search behavior and differences between expert and novice users. Our evaluation shows that textual search and content browsing are the most important aspects in terms of logged user interactions. Furthermore, we observe a trend towards deep learning based features, especially in the form of labels generated by artificial neural networks. But nevertheless, for some tasks, very specific content-based search features are still being used. We expect these findings to contribute to future improvements of Interactive Video search systems.
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on influential trends in Interactive Video retrieval Video browser showdown 2015 2017
IEEE Transactions on Multimedia, 2018Co-Authors: Jakub Lokoč, Werner Bailer, Klaus Schoeffmann, Bernd Muenzer, George AwadAbstract:The last decade has seen innovations that make Video recording, manipulation, storage, and sharing easier than ever before, thus impacting many areas of life. New Video retrieval scenarios emerged as well, which challenge the state-of-the-art Video retrieval approaches. Despite recent advances in content analysis, Video retrieval can still benefit from involving the human user in the loop. We present our experience with a class of Interactive Video retrieval scenarios and our methodology to stimulate the evolution of new Interactive Video retrieval approaches. More specifically, the Video browser showdown evaluation campaign is thoroughly analyzed, focusing on the years 2015–2017. Evaluation scenarios, objectives, and metrics are presented, complemented by the results of the annual evaluations. The results reveal promising Interactive Video retrieval techniques adopted by the most successful tools and confirm assumptions about the different complexity of various types of Interactive retrieval scenarios. A comparison of the Interactive retrieval tools with automatic approaches (including fully automatic and manual query formulation) participating in the TRECVID 2016 ad hoc Video search task is discussed. Finally, based on the results of data analysis, a substantial revision of the evaluation methodology for the following years of the Video browser showdown is provided.
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Interactive Video search tools a detailed analysis of the Video browser showdown 2015
Multimedia Tools and Applications, 2017Co-Authors: Claudiu Cobârzan, Werner Bailer, Klaus Schoeffmann, Wolfgang Hurst, Adam Blaźek, Jakub Lokoăź, Stefanos Vrochidis, Kai Uwe Barthel, Luca RossettoAbstract:Interactive Video retrieval tools developed over the past few years are emerging as powerful alternatives to automatic retrieval approaches by giving the user more control as well as more responsibilities. Current research tries to identify the best combinations of image, audio and text features that combined with innovative UI design maximize the tools performance. We present the last installment of the Video Browser Showdown 2015 which was held in conjunction with the International Conference on MultiMedia Modeling 2015 (MMM 2015) and has the stated aim of pushing for a better integration of the user into the search process. The setup of the competition including the used dataset and the presented tasks as well as the participating tools will be introduced . The performance of those tools will be thoroughly presented and analyzed. Interesting highlights will be marked and some predictions regarding the research focus within the field for the near future will be made.
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collaborative feature maps for Interactive Video search
Conference on Multimedia Modeling, 2017Co-Authors: Klaus Schoeffmann, Bernd Muenzer, Manfred Jurgen Primus, Stefan Petscharnig, Christof Karisch, Wolfgang HuerstAbstract:This extended demo paper summarizes our interface used for the Video Browser Showdown (VBS) 2017 competition, where visual and textual known-item search (KIS) tasks, as well as ad-hoc Video search (AVS) tasks in a 600-h Video archive need to be solved Interactively. To this end, we propose a very flexible distributed Video search system that combines many ideas of related work in a novel and collaborative way, such that several users can work together and explore the Video archive in a complementary manner. The main interface is a perspective Feature Map, which shows keyframes of shots arranged according to a selected content similarity feature (e.g., color, motion, semantic concepts, etc.). This Feature Map is accompanied by additional views, which allow users to search and filter according to a particular content feature. For collaboration of several users we provide a cooperative heatmap that shows a synchronized view of inspection actions of all users. Moreover, we use collaborative re-ranking of shots (in specific views) based on retrieved results of other users.
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a user centric media retrieval competition the Video browser showdown 2012 2014
IEEE MultiMedia, 2014Co-Authors: Klaus SchoeffmannAbstract:The Video Browser Showdown is an international competition in the field of Interactive Video search and retrieval. It is held annually as a special session at the International Conference on Multimedia Modeling (MMM). The Video Browser Showdown evaluates the performance of exploratory tools for Interactive content search in Videos in direct competition and in front of an audience. Its goal is to push research on user-centric Video search tools including Video navigation, content browsing, content interaction, and Video content visualization. This article summarizes the first three VBS competitions (2012-2014).
Werner Bailer - One of the best experts on this subject based on the ideXlab platform.
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Interactive Video retrieval in the age of deep learning detailed evaluation of vbs 2019
IEEE Transactions on Multimedia, 2021Co-Authors: Luca Rossetto, Ralph Gasser, Jakub Lokoč, Werner Bailer, Klaus Schoeffmann, Bernd Muenzer, Tomáš Souček, Phuong Anh Nguyen, Paolo Bolettieri, Andreas LeibetsederAbstract:Despite the fact that automatic content analysis has made remarkable progress over the last decade – mainly due to significant advances in machine learning – Interactive Video retrieval is still a very challenging problem, with an increasing relevance in practical applications. The Video Browser Showdown (VBS) is an annual evaluation competition that pushes the limits of Interactive Video retrieval with state-of-the-art tools, tasks, data, and evaluation metrics. In this paper, we analyse the results and outcome of the 8th iteration of the VBS in detail. We first give an overview of the novel and considerably larger V3C1 dataset and the tasks that were performed during VBS 2019. We then go on to describe the search systems of the six international teams in terms of features and performance. And finally, we perform an in-depth analysis of the per-team success ratio and relate this to the search strategies that were applied, the most popular features, and problems that were experienced. A large part of this analysis was conducted based on logs that were collected during the competition itself. This analysis gives further insights into the typical search behavior and differences between expert and novice users. Our evaluation shows that textual search and content browsing are the most important aspects in terms of logged user interactions. Furthermore, we observe a trend towards deep learning based features, especially in the form of labels generated by artificial neural networks. But nevertheless, for some tasks, very specific content-based search features are still being used. We expect these findings to contribute to future improvements of Interactive Video search systems.
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on influential trends in Interactive Video retrieval Video browser showdown 2015 2017
IEEE Transactions on Multimedia, 2018Co-Authors: Jakub Lokoč, Werner Bailer, Klaus Schoeffmann, Bernd Muenzer, George AwadAbstract:The last decade has seen innovations that make Video recording, manipulation, storage, and sharing easier than ever before, thus impacting many areas of life. New Video retrieval scenarios emerged as well, which challenge the state-of-the-art Video retrieval approaches. Despite recent advances in content analysis, Video retrieval can still benefit from involving the human user in the loop. We present our experience with a class of Interactive Video retrieval scenarios and our methodology to stimulate the evolution of new Interactive Video retrieval approaches. More specifically, the Video browser showdown evaluation campaign is thoroughly analyzed, focusing on the years 2015–2017. Evaluation scenarios, objectives, and metrics are presented, complemented by the results of the annual evaluations. The results reveal promising Interactive Video retrieval techniques adopted by the most successful tools and confirm assumptions about the different complexity of various types of Interactive retrieval scenarios. A comparison of the Interactive retrieval tools with automatic approaches (including fully automatic and manual query formulation) participating in the TRECVID 2016 ad hoc Video search task is discussed. Finally, based on the results of data analysis, a substantial revision of the evaluation methodology for the following years of the Video browser showdown is provided.
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Interactive Video search tools a detailed analysis of the Video browser showdown 2015
Multimedia Tools and Applications, 2017Co-Authors: Claudiu Cobârzan, Werner Bailer, Klaus Schoeffmann, Wolfgang Hurst, Adam Blaźek, Jakub Lokoăź, Stefanos Vrochidis, Kai Uwe Barthel, Luca RossettoAbstract:Interactive Video retrieval tools developed over the past few years are emerging as powerful alternatives to automatic retrieval approaches by giving the user more control as well as more responsibilities. Current research tries to identify the best combinations of image, audio and text features that combined with innovative UI design maximize the tools performance. We present the last installment of the Video Browser Showdown 2015 which was held in conjunction with the International Conference on MultiMedia Modeling 2015 (MMM 2015) and has the stated aim of pushing for a better integration of the user into the search process. The setup of the competition including the used dataset and the presented tasks as well as the participating tools will be introduced . The performance of those tools will be thoroughly presented and analyzed. Interesting highlights will be marked and some predictions regarding the research focus within the field for the near future will be made.
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the Video browser showdown a live evaluation of Interactive Video search tools
International Journal of Multimedia Information Retrieval, 2013Co-Authors: Klaus Schoeffmann, Werner Bailer, David Ahlstrom, Claudiu Cobârzan, Frank Hopfgartner, Kevin Mcguinness, Cathal Gurrin, Christian Frisson, Manfred Del Fabro, Hongliang BaiAbstract:The Video Browser Showdown evaluates the performance of exploratory Video search tools on a common data set in a common environment and in presence of the audience. The main goal of this competition is to enable researchers in the field of Interactive Video search to directly compare their tools at work. In this paper, we present results from the second Video Browser Showdown (VBS2013) and describe and evaluate the tools of all participating teams in detail. The evaluation results give insights on how exploratory Video search tools are used and how they perform in direct comparison. Moreover, we compare the achieved performance to results from another user study where 16 participants employed a standard Video player to complete the same tasks as performed in VBS2013. This comparison shows that the sophisticated tools enable better performance in general, but for some tasks common Video players provide similar performance and could even outperform the expert tools. Our results highlight the need for further improvement of professional tools for Interactive search in Videos.
Lynn D Wilcox - One of the best experts on this subject based on the ideXlab platform.
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hyper hitchcock authoring Interactive Videos and generating Interactive summaries
ACM Multimedia, 2003Co-Authors: Andreas Girgensohn, Frank M Shipman, Lynn D WilcoxAbstract:To simplify the process of editing Interactive Video, we developed the concept of "detail-on-demand" Video as a subset of general hyperVideo. Detail-on-demand Video keeps the authoring and viewing interfaces relatively simple while supporting a wide range of Interactive Video applications. Our editor, Hyper-Hitchcock, provides a direct manipulation environment in which authors can combine Video clips and place hyperlinks between them. To summarize a Video, Hyper-Hitchcock can also automatically generate a hyperVideo composed of multiple Video summary levels and navigational links between these summaries and the original Video. Viewers may Interactively select the amount of detail they see, access more detailed summaries, and navigate to the source Video through the summary.
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shared Interactive Video for teleconferencing
ACM Multimedia, 2003Co-Authors: Chunyuan Liao, Qiong Liu, Don Kimber, Patrick Chiu, Jonathan Foote, Lynn D WilcoxAbstract:We present a system that allows remote and local participants to control devices in a meeting environment using mouse or pen based gestures "through" Video windows. Unlike state-of-the-art device control interfaces that require interaction with text commands, buttons, or other artificial symbols, our approach allows users to interact with devices through live Video of the environment. This naturally extends our Video supported pan/tilt/zoom (PTZ) camera control system, by allowing gestures in Video windows to control not only PTZ cameras, but also other devices visible in Video images. For example, an authorized meeting participant can show a presentation on a screen by dragging the file on a personal laptop and dropping it on the Video image of the presentation screen. This paper presents the system architecture, implementation tradeoffs, and various meeting control scenarios.
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hyper hitchcock towards the easy authoring of Interactive Video
International Conference on Human-Computer Interaction, 2003Co-Authors: Frank M Shipman, Andreas Girgensohn, Lynn D WilcoxAbstract:To simplify the process of editing Interactive Video, we developed the concept of “detail-on-demand” Video as a subset of general hyperVideo where a single button press reveals additional information about the current Video sequence. Detail-on-demand Video keeps the authoring and viewing interfaces relatively simple while supporting a wide range of Interactive Video applications. Our editor, Hyper-Hitchcock, builds on prior work on automatic analysis to find the best quality Video clips. It introduces Video composites as an abstraction for grouping and manipulating sets of Video clips. Navigational links can be created between any two Video clips or composites. Such links offer a variety of return behaviors for when the linked Video is completed that can be tailored to different materials. Initial impressions from a pilot study indicate that Hyper-Hitchcock is easy to learn although the behavior of links is not immediately intuitive for all users.
Jakub Lokoč - One of the best experts on this subject based on the ideXlab platform.
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Interactive Video retrieval in the age of deep learning detailed evaluation of vbs 2019
IEEE Transactions on Multimedia, 2021Co-Authors: Luca Rossetto, Ralph Gasser, Jakub Lokoč, Werner Bailer, Klaus Schoeffmann, Bernd Muenzer, Tomáš Souček, Phuong Anh Nguyen, Paolo Bolettieri, Andreas LeibetsederAbstract:Despite the fact that automatic content analysis has made remarkable progress over the last decade – mainly due to significant advances in machine learning – Interactive Video retrieval is still a very challenging problem, with an increasing relevance in practical applications. The Video Browser Showdown (VBS) is an annual evaluation competition that pushes the limits of Interactive Video retrieval with state-of-the-art tools, tasks, data, and evaluation metrics. In this paper, we analyse the results and outcome of the 8th iteration of the VBS in detail. We first give an overview of the novel and considerably larger V3C1 dataset and the tasks that were performed during VBS 2019. We then go on to describe the search systems of the six international teams in terms of features and performance. And finally, we perform an in-depth analysis of the per-team success ratio and relate this to the search strategies that were applied, the most popular features, and problems that were experienced. A large part of this analysis was conducted based on logs that were collected during the competition itself. This analysis gives further insights into the typical search behavior and differences between expert and novice users. Our evaluation shows that textual search and content browsing are the most important aspects in terms of logged user interactions. Furthermore, we observe a trend towards deep learning based features, especially in the form of labels generated by artificial neural networks. But nevertheless, for some tasks, very specific content-based search features are still being used. We expect these findings to contribute to future improvements of Interactive Video search systems.
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on influential trends in Interactive Video retrieval Video browser showdown 2015 2017
IEEE Transactions on Multimedia, 2018Co-Authors: Jakub Lokoč, Werner Bailer, Klaus Schoeffmann, Bernd Muenzer, George AwadAbstract:The last decade has seen innovations that make Video recording, manipulation, storage, and sharing easier than ever before, thus impacting many areas of life. New Video retrieval scenarios emerged as well, which challenge the state-of-the-art Video retrieval approaches. Despite recent advances in content analysis, Video retrieval can still benefit from involving the human user in the loop. We present our experience with a class of Interactive Video retrieval scenarios and our methodology to stimulate the evolution of new Interactive Video retrieval approaches. More specifically, the Video browser showdown evaluation campaign is thoroughly analyzed, focusing on the years 2015–2017. Evaluation scenarios, objectives, and metrics are presented, complemented by the results of the annual evaluations. The results reveal promising Interactive Video retrieval techniques adopted by the most successful tools and confirm assumptions about the different complexity of various types of Interactive retrieval scenarios. A comparison of the Interactive retrieval tools with automatic approaches (including fully automatic and manual query formulation) participating in the TRECVID 2016 ad hoc Video search task is discussed. Finally, based on the results of data analysis, a substantial revision of the evaluation methodology for the following years of the Video browser showdown is provided.
Shanchwen Chang - One of the best experts on this subject based on the ideXlab platform.
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Interactive Video instruction improves the quality of dispatcher assisted chest compression only cardiopulmonary resuscitation in simulated cardiac arrests
Critical Care Medicine, 2009Co-Authors: Chihwei Yang, Huichih Wang, Wenchu Chiang, Chewei Hsu, Weitien Chang, Zuishen Yen, Matthew Hueiming, Shyrchyr Chen, Shanchwen ChangAbstract:Objective:Bystander cardiopulmonary resuscitation (CPR) significantly improves survival of cardiac arrest victims. Dispatch assistance increases bystander CPR, but the quality of dispatcher-assisted CPR remains unsatisfactory. This study was conducted to assess the effect of adding Interactive Video
