Content-based browsing of video sequences

Arman, Farshid; Depommier, R.; Hsu, Arding; Chiu, Ming-Yee

doi:10.1145/192593.192630

Cited by 166 publications

(85 citation statements)

References 14 publications

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“…Arman et al [12] use moment invariants combined with histogram intersection to detect shot changes. Moment invariants have properties such as invariance to scale change, rotation, and translation.…”

Section: Moment Invariantsmentioning

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: Moment Invariantsmentioning

confidence: 99%

“…Temporal and spatial subsampling [85] O(P + 5B) 36.45 [12] O(23P) Edge change ratio [90,77] O(26P) + 240.67 Edge-based contrast [56] O(25P) Histogram difference, edge points count, double chromatic difference [87] O(27P + 3N )…”

Section: 25mentioning

confidence: 99%

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

2003

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“…On the on hand, DCT coefficients are exploited. Arman et al [1] compare a subset of DCT coefficients of two successive I frames to calculate the frame differences as the coefficients in the frequency domain are mathematically related to the spatial domain. The temporal resolution of this type of techniques is low, resulting in an increased amount of false alarms when camera motion is present.…”

Section: General Techniquesmentioning

confidence: 99%

Compressed-Domain Shot Boundary Detection for H.264/AVC Using Intra Partitioning Maps

Bruyne

Cock

Poppe

et al. 2011

Lecture Notes in Computer Science

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Abstract. In this paper, a novel technique for shot boundary detection operating on H.264/AVC-compressed sequences is presented. Due to new and improved coding tools in H.264/AVC, the characteristics of the obtained sequences differ from former video coding standards. Although several algorithms working on this new standard are already proposed, the presence of IDR frames can still lead to a low accuracy for abrupt transitions. To solve this issue, we present the motion-compensated intra partitioning map which relies on the intra partitioning modes and the motion vectors present in the compressed video stream. Experimental results show that this motion-compensated map achieves a high accuracy and exceeds related work.

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“…Several existing examples of this implementation are found such as simply time-stamping the numeric time in each keyframe as in [19] [16] [15], displaying quantifiable objects to visualise shot length [20] …”

Section: The Provision Of Temporal Orientationmentioning

confidence: 99%

Implementation and Analysis of Several Keyframe-Based Browsing Interfaces to Digital Video

Lee

Smeaton

Berrut

et al. 2000

Research and Advanced Technology for Digital Libraries

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Abstract. In this paper we present a variety of browsing interfaces for digital video information. The six interfaces are implemented on top of Físchlár, an operational recording, indexing, browsing and playback system for broadcast TV programmes. In developing the six browsing interfaces, we have been informed by the various dimensions which can be used to distinguish one interface from another. For this we include layeredness (the number of "layers" of abstraction which can be used in browsing a programme), the provision or omission of temporal information (varying from full timestamp information to nothing at all on time) and visualisation of spatial vs. temporal aspects of the video. After introducing and defining these dimensions we then locate some common browsing interfaces from the literature in this 3-dimensional "space" and then we locate our own six interfaces in this same space. We then present an outline of the interfaces and include some user feedback.

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Content-based browsing of video sequences

Cited by 166 publications

References 14 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

Compressed-Domain Shot Boundary Detection for H.264/AVC Using Intra Partitioning Maps

Implementation and Analysis of Several Keyframe-Based Browsing Interfaces to Digital Video

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