A Temporal Video Segmentation and Summary Generation Method Based on Shots' Abrupt and Gradual Transition Boundary Detecting

Chen, Yinzi; Deng, Yan; Guo, Yunbo; Wang, Wendong; Zou, Yanming; Wang, Kongqiao

doi:10.1109/iccsn.2010.58

Cited by 4 publications

(8 citation statements)

References 7 publications

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“…Before content feature extraction can take place the raw media, in most cases, needs to be pre-processed to optimise the effectiveness and/or efficiency of the extraction process. Typically, the pre-processing is a filtering step to remove artefacts that could cause errors in the extraction process [Chen et al 2010;Yongquan et al 2009], and can be used to reduce the time or complexity of processing the features [Amiri and Fathy 2011;Chan and Wong 2011;. This is usually a case of normalising, converting or filtering the media in the pre-processing step.…”

Section: Raw Mediamentioning

confidence: 99%

“…This reduces the region into candidate areas that are likely to be foreground and background regions. In [Chen, Deng, Guo, Wang, Zou and Wang 2010] they transform the colour space profile from the H.264 YUV colour space, into a more humanly perceptible HSV colour space.…”

Section: Raw Mediamentioning

confidence: 99%

“…Greyscale or colour histogram-based features are relatively stable though they lack spatial information. While most systems use intensity [Mohanta, Saha and Chanda 2012] or RGB colour histogram [Ma et al 2012], some use other colour triplets, for example, YUV [Hameed 2009] or HSV palette [Chen, Deng, Guo, Wang, Zou and Wang 2010;Xu and Xu 2010]. When using colour histogram features, it is necessary to decode the compressed video streams firstly [Ma, Yu and Huang 2012].…”

Section: Syntactic Temporal Segmentationmentioning

confidence: 99%

“…When using colour histogram features, it is necessary to decode the compressed video streams firstly [Ma, Yu and Huang 2012]. Measuring the colour histogram difference is a good indicator of abrupt shot change and has provided high rate detection results [Chen, Deng, Guo, Wang, Zou and Wang 2010]. This can be affected by fast global motion, such as action scenes and quick pan and zoom and special effects.…”

Section: Syntactic Temporal Segmentationmentioning

confidence: 99%

“…In [Grana and Cucchiara 2007] they use a pixel based approach and histogram based approach in a unified linear transition decomposition. In [Chen, Deng, Guo, Wang, Zou and Wang 2010] they use two algorithms for shot detection, as each one negates the disadvantages of the other.…”

Section: Syntactic Temporal Segmentationmentioning

confidence: 99%

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MAC-REALM: A Video Content Feature Extraction and Modelling Framework

Parmar

Angelides

2015

The Computer Journal

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This paper discusses MAC-REALM, a framework for extraction of syntactic and semantic content features and content modelling with either little or no user interaction. The framework integrates a four filter-plane strategy: a pre-processing plane that filters redundant data, a syntactic feature extraction plane that filters syntactic features, a semantic relationships analysis and linkage plane that filters the spatial and temporal relationships of content features, and finally a content modelling plane where the syntactic and semantic content features are integrated into a content model. Each of the four planes is split into three layers: the content layer, where the content to be processed is stored, the application layer, where the content is converted into content descriptions, and the MPEG-7 layer, where content descriptions are serialized. Using MPEG-7 standards to produce the content model will provide wideranging interoperability, while facilitating granular multi-content type searches. MAC-REALM aims at 'bridging' the semantic gap, by integrating the syntactic and semantic content features from extraction through to modelling.

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Section: Raw Mediamentioning

confidence: 99%

Section: Raw Mediamentioning

confidence: 99%

Section: Syntactic Temporal Segmentationmentioning

confidence: 99%

Section: Syntactic Temporal Segmentationmentioning

confidence: 99%

Section: Syntactic Temporal Segmentationmentioning

confidence: 99%

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MAC-REALM: A Video Content Feature Extraction and Modelling Framework

Parmar

Angelides

2015

The Computer Journal

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Frame with significant perceived motion energy for mobile visual sensing system

Lin

Lian

2013

2013 IEEE International Conference on Information and Automation (ICIA)

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A Graph Representation Based Fuzzy C Means Approach to Video Summarization

Angadi

Naik²

2016

IJSPS

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The Video summarization normally includes shot boundary detection, key frame extraction from each shot and generation of summary. The proposed video summarization approach eliminates shot boundary detection by employing segmentation based key frame extraction scheme and the segmentation is achieved by fuzzy C Means (FCM) clustering. The video summarization algorithms basically perform structural analysis of the video. Recently algorithms utilizing graph theoretic approaches for structure analysis are found in literature. The proposed method models a video segment formed by FCM clustering as undirected weighted graph with frames in cluster as nodes of graph and Euclidean feature distance as edge weight. The eccentricity of each graph node is used to determine its connectivity to other nodes of the graph. If the eccentricity of node is greater than the mean eccentricity of graph that node is one of the important node and the frame represented by that node is selected as key frame. This is done over all the clusters and the summary is created using key frames and merging them on the basis of their timeline. This method ensures that video summary represents the most unique frames of the input video and gives equal attention to preserving continuity of the summarized video. The performance of the algorithm is evaluated for compactness, fidelity and informativeness measures.

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A Temporal Video Segmentation and Summary Generation Method Based on Shots' Abrupt and Gradual Transition Boundary Detecting

Cited by 4 publications

References 7 publications

MAC-REALM: A Video Content Feature Extraction and Modelling Framework

MAC-REALM: A Video Content Feature Extraction and Modelling Framework

Frame with significant perceived motion energy for mobile visual sensing system

A Graph Representation Based Fuzzy C Means Approach to Video Summarization

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