Interactive Evaluation of Video Browsing Tools

Int J Multimed Info Retr

Ahlström

Bailer

et al. 2013

Self Cite

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 compari- son. 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.

Section: Overall Performancementioning

confidence: 89%

The Video Browser Showdown: a live evaluation of interactive video search tools

Int J Multimed Info Retr

Ahlström

Bailer

et al. 2013

Self Cite

“…The server checks if the segment was found in the correct video and at the correct position and computes a score for the team, according to a formula that considers the search time (typically a value between 4 and 8 minutes) and the number of previously submitted wrong results for the search task (see [2,42]). According to these parameters a team can get up to 100 points for a correct solved task, and in worst case zero points for a wrong or unanswered task.…”

Section: Video Browser Showdown 2015mentioning

confidence: 99%

Interactive video search tools: a detailed analysis of the video browser showdown 2015

Cobârzan

Bailer

et al. 2016

Multimed Tools Appl

Self Cite

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 (2017) 76:5539-5571 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.

“…The advantage of uniform sampling is that it is quick and easy to implement because it requires no analysis of the content of the frames, and it provides a good coverage of the entire video. It has been used successfully for several applications, e.g., to summarize the content of a video [1]. It works by uniformly sampling frames from the video at equidistant positions.…”

Section: Uniform and Random Sampling As Baselinementioning

confidence: 99%

Keyframe extraction in endoscopic video

Fabro

Szkaliczki

et al. 2014

Multimed Tools Appl

Self Cite

In medical endoscopy more and more surgeons archive the recorded video streams in a long-term storage. One reason for this development, which is enforced by law in some countries, is to have evidence in case of lawsuits from patients. Another more practical reason is to allow later inspection of previous procedures and also to use parts of such videos for research and for training. However, due to the dramatic amount of video data recorded in a hospital on a daily basis, it is very important to have good preview images for these videos in order to allow for quick filtering of undesired content and for easier browsing through such a video archive. Unfortunately, common shot detection and keyframe extraction methods cannot be used for that video data, because these videos contain unedited and highly similar content, especially in terms of color and texture, and no shot boundaries at all. We propose a new keyframe extraction approach for this special video domain and show that our method is significantly better than a previously proposed approach.