Performance characterization of video-shot-change detection methods

Gargi, Ullas; Kasturi, Rangachar; Strayer, S.H.

doi:10.1109/76.825852

Cited by 374 publications

(185 citation statements)

References 24 publications

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“…Finally some papers are reviewing only a specific kind of methods, as those from Gargi et al [31,32] which are respectively dedicated to colour histogram-based methods and MPEG and motion-based methods for temporal segmentation of video. Mandal et al [59] focused on methods working in compressed domain.…”

Section: Related Workmentioning

confidence: 99%

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A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval

2003

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We present in this paper a review of methods for segmentation of uncompressed video sequences. Video segmentation is usually performed in the temporal domain by shot change detection. In case of real-time segmentation, computational complexity is one of the criteria which has to be taken into account when comparing different methods. When dealing with uncompressed video sequences, this criterion is even more significant. However previous published reviews did not involve complexity criterion when comparing shot change detection methods. Only recognition rate and ability to classify detected shot changes were considered. So contrary to previous reviews we give here complexity of most of the described methods. We review in this paper an extensive set of methods presented in the literature and classify them in several parts, depending on the information used to detect shot changes. The earliest methods were comparing successive frames by relying on most simple elements, that is to say pixels. Comparison could be performed on a global level, so methods based on histograms were also proposed. Block-based methods have been considered to process data at an intermediate level, between local (using pixels) and global (using histograms) levels. More complex features can be involved, resulting in feature-based methods. Alternatively some methods rely on motion as a criterion to detect shot changes. Finally different kinds of information could be combined together in order to increase the quality of shot change detection. So our review will detail segmentation methods

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Section: Related Workmentioning

confidence: 99%

“…The number of shot change detection methods is now important and several reviews of these methods have been done [3,42,17,7,48,57,44,14,56,22,88,31,32,59]. These reviews often present the different methods and their efficiency based on some quality measures.…”

Section: Introductionmentioning

confidence: 99%

A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval

2003

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“…Systems that are capable of segmenting video and extracting key frames that summarize the video content can substantially simplify browsing these databases over a network and retrieving important content. An analysis of the performances of early shot change detection algorithms is given in [23]. The methods analyzed in [23] can be categorized into two major groups: i) methods based on histogram distances, and ii) methods based on variations of MPEG coefficients.…”

Section: Example 1: Video Segmentationmentioning

confidence: 99%

“…An analysis of the performances of early shot change detection algorithms is given in [23]. The methods analyzed in [23] can be categorized into two major groups: i) methods based on histogram distances, and ii) methods based on variations of MPEG coefficients. A comprehensive study is given in [24] where a formal framework for evaluation is also developed.…”

Section: Example 1: Video Segmentationmentioning

confidence: 99%

The Role of Dynamics in Extracting Information Sparsely Encoded in High Dimensional Data Streams

Sznaier

Camps

Özay

et al. 2010

Dynamics of Information Systems

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Summary. A major roadblock in taking full advantage of the recent exponential growth in data collection and actuation capabilities stems from the curse of dimensionality. Simply put, existing techniques are ill-equipped to deal with the resulting overwhelming volume of data. The goal of this chapter is to show how the use of simple dynamical systems concepts can lead to tractable, computationally efficient algorithms for extracting information sparsely encoded in multimodal, extremely large data sets. In addition, as shown here, this approach leads to non-entropic information measures, better suited than the the classical, entropy-based information theoretic measure, to problems where the information is by nature dynamic and changes as it propagates through a network where the nodes themselves are dynamical systems.

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“…However, it is quite difficult to give a precise definition of a video shot transition since many factors such as camera motions may change the video content significantly. Usually, a shot is defined to be a sequence of frames that appears to be continuously captured by the same camera [2].…”

Section: Introductionmentioning

confidence: 99%

A Shot Boundary Detection Technique Based on Local Color Moments in YCbCr Color Space

Angadi¹,

Naik²

2012

Computer Science &Amp; Information Technology (CS &Amp; IT)

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Performance characterization of video-shot-change detection methods

Cited by 374 publications

References 24 publications

A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval

A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval

The Role of Dynamics in Extracting Information Sparsely Encoded in High Dimensional Data Streams

A Shot Boundary Detection Technique Based on Local Color Moments in YCbCr Color Space

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