- General Chairs:
- Paul Over,
- Alan F. Smeaton
It is our great pleasure to welcome you to the first TRECVID Video Summarization workshop, held in conjunction with ACM Multimedia 2007. Although this is the first TRECVID summarization workshop, it is only the next in an annual series of TRECVID evaluation workshops going back to 2001. TRECVID is an annual event whereby the effectiveness of tasks relative to content-based video management is benchmarked in an open, metrics-based forum. TRECVID attracts over 60 research groups from across the world each year in an activity in which those groups can assess the relative effectiveness of their techniques against the best in the world. TRECVID has been instrumental in helping to push back the boundaries in tasks like shot boundary detection, video search and automatic concept/feature detection and has been a catalyst in helping the research community to achieve improvements in each of these in recent years.
This year is the first year that TRECVID has addressed the task of automatic video summarization and in this workshop we shall see the results of 22 research groups from 14 countries as they address the challenge of automatically summarizing raw, unprocessed rushes video down to at most 4% of the original content duration. This is also the first year that TRECVID has held one of its workshops outside the closed confines of the NIST campus in Gaithersburg, USA. We are delighted that doing this gives us the opportunity to showcase our collective activities to a wider audience, not just our own participants, and we believe that collocating with the ACM Multimedia conference is an ideal forum for this. We thank the ACM Multimedia workshop chairs for affording us this opportunity.
The TRECVID summarization workshop is not like any other workshop in that many or most of the workshop participants will have worked to complete a shared task, namely the automatic summarization of a collection of input videos. This means that we expect to have a highly interactive, highly involved workshop with much offline discussion and idea brainstorming. We are looking forward to it.
Proceeding Downloads
The trecvid 2007 BBC rushes summarization evaluation pilot
This paper provides an overview of a pilot evaluation of video summaries using rushes from several BBC dramatic series. It was carried out under the auspices of TRECVID. Twenty-two research teams submitted video summaries of up to 4% duration, of 42 ...
Video summarization at Brno University of Technology
- Vitêzslav Beran,
- Michal Hradiš,
- Adam Herout,
- Stanislav Sumec,
- Igor Potúček,
- Pavel Zemčik,
- Josef Mlích,
- Aleš Láník,
- Petr ChmelaƊ
This paper describes the video summarization system built for the TRECVID 2007 evaluation by the Brno team. Motivations for the system design and its overall structure are described followed by more detailed description of the critical parts of the ...
Clever clustering vs. simple speed-up for summarizing rushes
- Alexander G. Hauptmann,
- Michael G. Christel,
- Wei-Hao Lin,
- Bryan Maher,
- Jun Yang,
- Robert V. Baron,
- Guang Xiang
This paper discusses in detail our approaches for producing the submitted summaries to TRECVID, including the two baseline methods. The cluster method performed well in terms of coverage, and adequately in terms of user satisfaction, but did take longer ...
Rushes video summarization by object and event understanding
This paper explores a variety of visual and audio analysis techniques in selecting the most representative video clips for rushes summarization at TRECVID 2007. These techniques include object detection, camera motion estimation, keypoint matching and ...
Generating comprehensible summaries of rushes sequences based on robust feature matching
This paper describes our first attempt at tackling a pilot task in Trecvid: video summarization of rushes data [3]. Our method is based on the tight clustering produced via SIFT matching. In this first attempt, we try to examine how our approach ...
A user-centered approach to rushes summarisation via highlight-detected keyframes
- Daragh Byrne,
- Peter Kehoe,
- Hyowon Lee,
- Ciarán Ó. Conaire,
- Alan F. Smeaton,
- Noel E. O'Connor,
- Gareth J.F. Jones
We present our keyframe-based summary approach for BBC Rushes video as part of the TRECVid Summarisation benchmark evaluation carried out in 2007. We outline our approach to summarisation that uses video processing for feature extraction and is informed ...
Video summarization preserving dynamic content
This paper describes a system for selecting excerpts from unedited video and presenting the excerpts in a short summary video for efficiently understanding the video contents. Color and motion features are used to divide the video into segments where ...
Rushes summarization with self-organizing maps
In this paper, we describe our approach for video summarization that was applied to the BBC rushes material as part of the TRECVID 2007 evaluations. The method consists of initial shot boundary detection followed by shot similarity assessment and ...
The Hong Kong Polytechnic University at TRECVID 2007 BBC rushes summarization
In this paper, we propose the framework and methodology for BBC rushes summarization task of TRECVID 2007. We divide the entire task into three sub-tasks: shot segmentation; noise shot detection and removal; video summarization. We first segment the ...
Split-screen dynamically accelerated video summaries
In this paper, we describe our approach to the TRECVID 2007 BBC Rushes Summarization task. Our processing is composed of several steps. First the video is segmented into shots. Then, one-second video segments are clustered into similarity classes. The ...
Skimming rushes video using retake detection
In audiovisual post-production users are confronted with large amounts of redundant unedited raw material, called rushes. Viewing and organizing this material is a crucial but time consuming task. This paper describes an approach for creating skimmed ...
Video rushes summarization by adaptive acceleration and stacking of shots
When witnessing the great increase of video data available, it becomes clear that summarization is one of the great challenges ahead. One particular problem is the summarization of video rushes.
In this paper we present a straightforward approach that ...
National institute of informatics, japan at TRECVID 2007: BBC rushes summarization
In this paper, we present a method for BBC rushes summarization. In the proposed method, first the input video is decomposed into fragments by comparing consecutive frames. Next, these fragments are grouped by a clustering method. Using the clustering ...
NTU TRECVID-2007 fast rushes summarization system
Rushes are the raw materials used to produce a video. They often contain redundant and repetitive contents. Rushes summarization aims to provide a quick overview for a rushes video. As part of TRECVID 2007, NIST initiates a rushes summarization task. ...
THU-ICRC at rush summarization of TRECVID 2007
In this paper, we describe the THU-ICRC system for the rush summarization task of TRECVID07. Our main objective is to abstract a minimal length rush video by removing useless (or low-quality) and redundant frames and reserving important objects and ...
Feature fusion and redundancy pruning for rush video summarization
This paper presents a video summarization technique for rushes that employs high-level feature fusion to identify segments for inclusion. It aims to capture distinct video events using a variety of features: k-means based weighting, speech, camera ...
Attention-based video summarisation in rushes collection
This paper presents the framework of a general video summarisation system on the rushes collection, which formalises the summarisation process as an 0-1 Knapsack optimisation problem. Three stages are included, namely content analysis, content selection ...
On-line video skimming based on histogram similarity
This paper describes the method proposed for the TRECVID 2007 BBC rushes summarization task. Such method has been developed starting from an on-line summary generation approach which provides a fast way to generate a base summary that can be later ...
Cited By
- Bai L, Hu Y, Lao S, Smeaton A and O'Connor N (2010). Automatic summarization of rushes video using bipartite graphs, Multimedia Tools and Applications, 49:1, (63-80), Online publication date: 1-Aug-2010.
-
Rüger S (2010). Multimedia Information Retrieval, 10.1007/978-3-031-02269-2,
- Bailer W, Lee F and Thallinger G (2008). A distance measure for repeated takes of one scene, The Visual Computer: International Journal of Computer Graphics, 25:1, (53-68), Online publication date: 3-Dec-2008.
- Escalante H, Hérnadez C, Sucar L and Montes M Late fusion of heterogeneous methods for multimedia image retrieval Proceedings of the 1st ACM international conference on Multimedia information retrieval, (172-179)
Index Terms
- Proceedings of the international workshop on TRECVID video summarization