A motion-based scene tree for browsing and retrieval of compressed videos

Huang, Yi; Rajan, Dinesh; Chia, Liang-Tien

doi:10.1016/j.is.2005.12.005

Cited by 17 publications

(2 citation statements)

References 34 publications

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“…A scene is a set of shots and a boundary of one of these shots becomes a scene boundary. There are many studies to detect a scene boundary that mainly analyzes visual features and group shots according to the visual shot similarity [4,9,10,11,15,16]. Even though this approach can be applied to various domains due to the use of only visual features, visual similarities between shots have often seen in low quality.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Script-Subtitles Alignment to Scene Boundary Dectection in Movie

Park

Kim

et al. 2010

2010 IEEE International Symposium on Multimedia

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A movie, a typical multimedia data, includes several textual information such as subtitles and annotation texts as well as audio-visual information. In general, a story of a movie is progressed by dialogues of characters and the dialogues are produced based on a pre-written script that contains detailed descriptions of all the information related to the movie. The script consists of scene headings, character names, dialogues, actions, and so on. Rich information related to the movie can be extracted easily and accurately from each component of the script. However, since the script does not contain time information, additional processes are required to synchronize the script with the movie. The subtitle is usually made from the script's dialogue and has time information to display text on screen when the characters speak. Therefore, synchronization between the script and the movie can be accomplished through an alignment process between the script's dialogue and its' subtitle. In this paper, we propose a unique method of scene boundary detection exploited scriptsubtitles alignment. By synchronizing the script to movie, we identify scene boundaries with semantic level. In addition, we build a thesaurus to enhance alignment performance. Experimental results with real movies show that the proposed method can successfully, not only align scripts with those subtitles, but also detect scene boundaries.

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Section: Introductionmentioning

confidence: 99%

Exploiting Script-Subtitles Alignment to Scene Boundary Dectection in Movie

Park

Kim

et al. 2010

2010 IEEE International Symposium on Multimedia

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“…This approach highly reduces the time and man-power required during the indexing stage. The systems inroduced in [10,7] perform video retrieval according to some similarity measurements between video shots. Although, it has been demonstrated that this approach can give excellent results, user is usually required to provide a sample video clip, which may not be always possible.…”

Section: Introductionmentioning

confidence: 99%

Object-Based Surveillance Video Retrieval System with Real-Time Indexing Methodology

Yuk

Wong

Chung

et al.

Lecture Notes in Computer Science

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Abstract. This paper presents a novel surveillance video indexing and retrieval system based on object features similarity measurement. The system firstly extracts moving objects from the videos by an efficient motion segmentation method. The fundamental features of each moving object are then extracted and indexed into the database. During retrieval, the system matches the query with the features indexed in the database without re-processing the videos. Video clips which contain the objects with sufficiently high relevance scores are then returned. The novelty of the system includes: 1. A real-time automatic indexing methodology achieved by a fast motion segmentation, such that the system is able to perform on-the-fly indexing on video sources; and 2. an object-based retrieval system with fundamental features matching approach, which allows user to specify the query by providing an example image or even a sketch of the desired objects. Such an approach can search the desired video clips in a more convenient and unambiguous way comparing with traditional text-based matching.

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