Video browsing interfaces and applications: a review

Schoeffmann, Klaus; Hopfgartner, Frank; Marques, Oge; Boeszoermenyi, Laszlo; Jose, Joemon M.

doi:10.1117/6.0000005

Cited by 52 publications

(48 citation statements)

References 81 publications

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“…A typical video browsing tool -although a very simple one -is a common video player that provides navigation facilities for changing the playback position in a video (e.g., with a seeker-bar). Many browsing tools, with better interaction means than provided by a typical video player, have been presented in the literature (for a detailed review see [29]). While many of them are advanced navigation methods (e.g., [7,8]), extended video players (e.g., [10,14,18]) or enhanced video content visualizations [6], some are highly sophisticated browsing tools (e.g., [1,25,30]).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Schoeffmann

Ahlström

Bailer

et al. 2013

Int J Multimed Info Retr

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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.

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Section: Introductionmentioning

confidence: 99%

“…Although many tools have been proposed for interactive video search (see [29]), it is not obvious how well these tools perform for specific search tasks and for specific user groups such as expert and novice users [32,37]. It is also non-trivial to directly compare the tools without a common user study.…”

Section: Introductionmentioning

confidence: 99%

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

Schoeffmann

Ahlström

Bailer

et al. 2013

Int J Multimed Info Retr

Self Cite

View full text Add to dashboard Cite

show abstract

“…The user can browse through the abstract representations to locate the desired videos. A detailed review on video browsing interfaces, and applications can be found in (Schoeffmann et al, 2010). There are two basic strategies to show the retrieval results.…”

Section: Shot Boundaries Are Fundamental Units Of Videosmentioning

confidence: 99%

Content Based Video Retrieval Based on HDWT and Sparse Representation

Mohamadzadeh

Farsi

2016

Image Anal Stereol

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Video retrieval has recently attracted a lot of research attention due to the exponential growth of video datasets and the internet. Content based video retrieval (CBVR) systems are very useful for a wide range of applications with several type of data such as visual, audio and metadata. In this paper, we are only using the visual information from the video. Shot boundary detection, key frame extraction, and video retrieval are three important parts of CBVR systems. In this paper, we have modified and proposed new methods for the three important parts of our CBVR system. Meanwhile, the local and global color, texture, and motion features of the video are extracted as features of key frames. To evaluate the applicability of the proposed technique against various methods, the P(1) metric and the CC_WEB_VIDEO dataset are used. The experimental results show that the proposed method provides better performance and less processing time compared to the other methods.Keywords: content based video retrieval (CBVR), Hadamard matrix and discrete wavelet transform (HDWT), key frame extraction, shot boundary detection, sparse representation.

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“…The video browsing and associated problem has been investigated by the research community for decades, [72]. However, the growing use of 3D video and the specific characteristics of this type of visual information make 3D video browsing a more interesting and challenging problem.…”

Section: Video Browsingmentioning

confidence: 99%

“…For example, once an interesting topic has been identified through display of the key-frames, a simple operation as a click on the respective key-frame can initiate video playback of the original content at that particular instant. Many video browsing methods have been proposed for 2D video [72]. However, to the best of the authors' knowledge, in the case of 3D video there are no works reported in the literature.…”

Section: Video Browsingmentioning

confidence: 99%

Towards key-frame extraction methods for 3D video: a review

Ferreira

Cruz

Assunção

2016

J Image Video Proc.

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The increasing rate of creation and use of 3D video content leads to a pressing need for methods capable of lowering the cost of 3D video searching, browsing and indexing operations, with improved content selection performance. Video summarisation methods specifically tailored for 3D video content fulfil these requirements. This paper presents a review of the state-of-the-art of a crucial component of 3D video summarisation algorithms: the key-frame extraction methods. The methods reviewed cover 3D video key-frame extraction as well as shot boundary detection methods specific for use in 3D video. The performance metrics used to evaluate the key-frame extraction methods and the summaries derived from those key-frames are presented and discussed. The applications of these methods are also presented and discussed, followed by an exposition about current research challenges on 3D video summarisation methods.Keywords: 3D key-frames extraction, 3D video summarisation, Shot boundary detection ReviewIn the last years, new features have been implemented in video applications and terminal equipments due to users demand, who are always seeking for new viewing experiences more interactive and immersive, such as those provided by 3D video. This new visual experience is created by depth information that is part of 3D video and absent in classic 2D video. The inclusion of depth information in video signals is not a recent innovation, but the interest in this type of content and aspects related to it, such as acquisition, analysis, coding, transmission and visualisation, have been increasing recently [1,2]. Lately, 3D video has been attracting attention from industry, namely content producers, equipment providers, distributors and from the research community mostly on account of the improvements in Quality of Experience that it provides to viewers [3], as well as due to the new business opportunities presented by this emerging multimedia format. In the past, video repositories were relatively small so that indexing and retrieval operations were easy to perform. More recently, the massification of 3D video and its applications have resulted in the generation of huge amounts of data, increasing the need for methods that can efficiently index, search, browse and summarise the relevant information with minimum human intervention. Furthermore, 3D video description and management is also required to enable quick presentation of the most important information in a user-friendly manner [4,5]. Video summarisation is a video-content representation method that can fulfil these requirements. In contrast to summarisation of 2D video, which has been the subject of a significant amount of research, 3D video summarisation is still a relatively unexplored research problem which deserves more attention.A video summary is a short version of a full-length video that preserves the essential visual and semantic information of the original unabridged content. In the video summarisation process, a subset of key-frames or a set of shorter video...

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Video browsing interfaces and applications: a review

Cited by 52 publications

References 81 publications

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

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

Content Based Video Retrieval Based on HDWT and Sparse Representation

Towards key-frame extraction methods for 3D video: a review

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