Video scene segmentation and semantic representation using a novel scheme

Zhu, Shiping; Liu, Yuncai

doi:10.1007/s11042-008-0233-0

Cited by 31 publications

(15 citation statements)

References 27 publications

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“…Such a result is quite competitive with the state of the art techniques introduced in (Rasheed et al, 2005), (Chasanis et al, 2009), (Zhu et al, 2009) which yield precision/recall rates varying between 65% and 72%.…”

Section: Figure 13 [Detected Scenes]mentioning

confidence: 93%

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Video Segmentation and Structuring for Indexing Applications

Țapu

Zaharia

2013

Multimedia Data Engineering Applications and Processing

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This paper introduces a complete framework for temporal video segmentation. First, a computationally efficient shot extraction method is introduced, which adopts the normalized graph partition approach, enriched with a non-linear, multiresolution filtering of the similarity vectors involved. The shot boundary detection technique proposed yields high precision (90%) and recall (95%) rates, for all types of transitions, both abrupt and gradual. Next, for each detected shot, the authors construct a static storyboard by introducing a leap keyframe extraction method. The video abstraction algorithm is 23% faster than existing techniques for similar performances. Finally, the authors propose a shot grouping strategy that iteratively clusters visually similar shots under a set of temporal constraints. Two different types of visual features are exploited: HSV color histograms and interest points. In both cases, the precision and recall rates present average performances of 86%.

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Section: Figure 13 [Detected Scenes]mentioning

confidence: 93%

“…The validation of our scene extraction method has been performed on a corpus of 6 sitcoms and 6 Hollywood movies (Tables 6 and 7) also used for evaluation purposes in the state of the art algorithms presented in (Rasheed et al, 2005), (Chasanis et al, 2009), (Zhu et al, 2009). Fig.…”

Section: Scene/dvd Chapter Extractionmentioning

confidence: 99%

Video Segmentation and Structuring for Indexing Applications

Țapu

Zaharia

2013

Multimedia Data Engineering Applications and Processing

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“…For example, [23] proposes a novel approach to video temporal decomposition into semantic scenes jointly exploiting lowlevel and high-level features automatically extracted from the visual and the auditory channel, where a fast scene transition graph (STG) approximation and a generalized STG-based technique are proposed for multimodal scene segmentation. [31] focuses on grouping video content into semantic segments and classifying semantic scenes into different types based on the temporal constraint of video content and visual similarity between shot activities. A novel work [20] proposes a method for automatic storyboard segmentation of TV news using image retrieval techniques and content manipulation, where image re-ranking based on neighborhood relations and temporal variance of image locations is adopted to construct a unimodal cluster for anchorperson detection and differentiation.…”

Section: Related Workmentioning

confidence: 99%

Content-based unsupervised segmentation of recurrent TV programs using grammatical inference

Vallet

Carrive

et al. 2017

Multimed Tools Appl

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TV program segmentation raised as a major topic in the last decade for the task of high quality indexing of multimedia content. Earlier studies of TV program segmentation are either highly supervised (e.g., event detection) or too specific to a certain type of program (e.g., cluster-based methods), which is not practically usable for indexing tasks because of the lack of generality of programs types. In this paper, we address the problem of unsupervised TV program segmentation by leveraging grammatical inference, i.e., discovering a common structural model shared by a collection of episodes of a recurrent TV program by finding an optimal alignment of structural elements across episodes. Structural elements referring to a video segment with a particular syntactic meaning with respect to the video structure. The use of symbolic representation of structural elements makes grammatical inference feasible to be applied on TV program modeling, and makes TV program segmentation possible to rely on only minimal domain knowledge. The proposed approach is operated in two phases. The first phase aims at obtaining a symbolic representation of each episode, where the elements relevant to the structure are discovered based on recurrence mining. The second phase is that of grammatical inference from the symbolic representation of episodes. We investigate two inference techniques, one based on multiple sequence alignment and one relying on uniform resampling, to infer structural grammars for TV programs. A model of the structure is derived from the structural grammars and used to predict the structure of new episodes. Comparative evaluation on two gramBingqing Qu

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“…• Abordagem baseada em agrupamento de tomadas: considera que uma cenaé formada por um conjunto de tomadas similares semanticamente, os trabalhos que fazem uso desse método utilizam essa similaridade entre as tomadas para fornecer algum vestígio ou indício de agrupamento (Cao, 2007;Zhu & Liu, 2009;Dunlop, 2010;Zeng et al, 2010).…”

Section: Características Visuaisunclassified

“…Relacionado ao agrupamento de tomadas, técnicas de textura de CBIR como a Transformada Discreta de Wavelet foi empregada por Zhu & Liu (2009) Zhu & Liu (2008b) detectaram e removeram os quadros-chave que não possuiam informaçãoútil por intermédio da técnica de comparação com um modelo (do inglês, template matching), detectando cenas a partir da similaridade visual e temporal das tomadas que não tiveram seus quadros-chave excluídos. Os níveis de precisão e revocação ficaram acima de 80% tendo como base de dados um vídeo de entrevistas e quatro filmes de ação.…”

Section: Características Visuaisunclassified

Segmentação de cenas em telejornais: uma abordagem multimodal

Coimbra¹

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Video scene segmentation and semantic representation using a novel scheme

Cited by 31 publications

References 27 publications

Video Segmentation and Structuring for Indexing Applications

Video Segmentation and Structuring for Indexing Applications

Content-based unsupervised segmentation of recurrent TV programs using grammatical inference

Segmentação de cenas em telejornais: uma abordagem multimodal

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