Efficient scalable coding of video summaries using dynamic GOP structures

Ferreira, Lino; Cruz, Luís A. da Silva; Assunção, Pedro

doi:10.1109/eurocon.2011.5929277

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…Despite the fact that several previous works addressed scalable summarisation for 2D video, e.g. [88,89], such methods were not extended to 3D and multiview, which leads to open research questions.…”

Section: Sbd and Key-frame Extraction Methodsmentioning

confidence: 99%

“…In the past, the problem of scalable coding of video summaries was addressed in [88,[92][93][94]. In [92] the authors propose a hierarchical frame selection scheme which considers semantic relevance in video sequences at different levels computed from compressed wavelet-based scalable video.…”

Section: Video Summary Codingmentioning

confidence: 99%

“…In [93], a method to generate video summaries from scalable video streams based on motion information is presented; while in [94], the authors propose to partition a video summary into summarisation units related by the prediction structure and independently decodable. Ferreira et al in [88] proposed a method to encode an arbitrary video summary using dynamic GOP structures in scalable streams. The scalable stream obtained was fully compatible with the scalable extension of the H.264/AVC standard.…”

Section: Video Summary Codingmentioning

confidence: 99%

See 2 more Smart Citations

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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Section: Sbd and Key-frame Extraction Methodsmentioning

confidence: 99%

Section: Video Summary Codingmentioning

confidence: 99%

Section: Video Summary Codingmentioning

confidence: 99%

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

Ferreira

Cruz

Assunção

2016

J Image Video Proc.

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“…Alternatively to this solution, the dynamic programming method was used to solve the priority ratio-distortion concealment optimization problem by breaking it down into simpler subproblems in a recursive manner [19]. In a previous work a similar method was used for different purpose [20]. The concealment distortion stage D k t is defined as the minimum total concealment distortion incurred by HP picture set that has t pictures and ends with the picture f k (l t−1 = k).…”

Section: Dynamic Programming Solutionmentioning

confidence: 99%

Optimal priority MDC video streaming for networks with path diversity

Correia

Ferreira

Assunção

et al. 2012

2012 International Conference on Telecommunications and Multimedia (TEMU)

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This paper proposes a robust video streaming scheme for priority networks with path diversity, based on a combined approach of multiple description coding (MDC) with optimal picture classification into two priorities. A binary classification algorithm is proposed to define high (HP) and low (LP) priority network abstraction layer units (NALU), which in turn define the packet priorities. An optimisation algorithm is used to find HP pictures, based on dynamic programming and relying on minimisation of the packet loss concealment distortion. The paper shows that the proposed algorithm is able to effectively improve the decoded video without increasing the MDC stream redundancy. The overall performance evaluation, carried out by simulating MDC video streaming over lossy networks with path diversity, demonstrates that the proposed algorithm yields higher video quality for a wide range of packet loss rates (PLR). Comparing with no-priority MDC video streaming schemes, the simulation results show that the proposed algorithm can improve the average PSNR results in 0.7-3.2dB for packet loss rates between 3% and 15%.

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Optimal GOP Size of H.264/AVC Temporal Scalable Coding

Tang

Yang

2013

Advances in Intelligent Systems and Applications - Volume 2

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Efficient scalable coding of video summaries using dynamic GOP structures

Cited by 4 publications

References 9 publications

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

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

Optimal priority MDC video streaming for networks with path diversity

Optimal GOP Size of H.264/AVC Temporal Scalable Coding

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