Annotation based personalized adaptation and presentation of videos for mobile applications

Bruyne, Sarah De; Hosten, Peter; Concolato, Cyril; Asbach, Mark; Cock, Jan De; Unger, Michael; Feuvre, Jean Le; Walle, Rik Van de

doi:10.1007/s11042-010-0575-2

Cited by 7 publications

(5 citation statements)

References 34 publications

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“…Different adaptation priorities can be assigned to different portions of video. 7,8 The limitation of this line of approach lies in its difficulty in correctly identifying ROIs. To perform semantic adaptation, automatic video content analysis either by annotation or by cropping and scaling certain regions of video is required.…”

Section: Published By Atlantis Pressmentioning

confidence: 99%

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Context-Aware Multimedia Content Adaptation for Mobile Web

Zhang¹,

Jangam²,

Zhou³

et al. 2015

IJNDC

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Multimedia content in web pages poses a variety of problems to mobile web users, such as incompatibility with mobile devices or failing to meet accessibility needs of users with vision disabilities. To address those problems, this study proposes and evaluates a context-aware approach to multimedia content adaptation for mobile Web. It uniquely takes into consideration not only users' preferences and accessibility needs, but also capabilities of multimedia support of specific mobile devices. Evaluation shows that the proposed approach is accurate and efficient. This study provides insights for research on context-aware mobile computing, adaptive interfaces, and mobile HCI.

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Section: Published By Atlantis Pressmentioning

confidence: 99%

“…Bruyne et al propose an approach that performs semantic analysis and adaptation at a presentation layer. 7 In another study, researchers propose a mechanism to process video content based on semantic preferences set by users. 8 Video is viewed as a set of semantic entities, with each having some relationship with others.…”

Section: Published By Atlantis Pressmentioning

confidence: 99%

Context-Aware Multimedia Content Adaptation for Mobile Web

Zhang¹,

Jangam²,

Zhou³

et al. 2015

IJNDC

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“…In this paper, our work reuses this concept but this paper adds the integration of different media elements, including video in the adaptation algorithm. Also, in previous work [6], we use the concept of scalable documents to achieve adaptation. Finally, we can also note that the MPEG-21 standard has addressed the problem of multimedia content adaptation through the Digital Item Adaptation standard.…”

Section: Related Workmentioning

confidence: 99%

“…This first document points to the video stream and adds a graphical interactive stream on top of the video. This part of our work is already described in [6].…”

mentioning

confidence: 99%

Adaptive video and metadata display using multimedia documents

Concolato

2010

Proceedings of the 2010 ACM Workshop on Social, Adaptive and Personalized Multimedia Interaction and Access

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Adaptation of multimedia content is a problem which has been addressed from different points of view in existing works. The specific problem of adapting multimedia documents which describe the spatial, temporal and interactive organization of several media elements such as video, text, images and graphics is still an open problem. In this paper, we present a system capable of generating adaptive multimedia documents, based on templates, for the display of video content, annotated with information such as regions of interest, images and descriptive text. We present how we designed our templates, their structure and the adaptation logic, based on JavaScript. Some results are presented and analyzed.

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“…• Spatial semantic adaptation of video, such that a high priority is attached to regions of interest to maximize the quality of the adapted content while targeting Universal Multimedia Access (Bruyne et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Fine‐granularity semantic video annotation

El-Khoury

Jergler

Bayou

et al. 2013

International Journal of Pervasive Computing and Communications

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A fine-grained video content indexing, retrieval, and adaptation requires accurate metadata describing its structure and semantics to the lowest granularity, i.e., the object level. We address these requirements by proposing Semantic Video Content Annotation Tool (SVCAT) for structural and high-level semantic annotation. SVCAT is a semi-automatic MPEG-7 standard compliant annotation tool, which produces metadata according to a new object-based video content model. Videos are temporally segmented into shots and shots level concepts are detected automatically using ImageNet as a background knowledge. These concepts are used as a guide to easily locate and select objects of interest which can be tracked automatically. The integration of shot based concept detection with object localization and tracking drastically alleviates the task of an annotator. As such, SVCAT enables to easily generate selective and fine-grained metadata which are vital for user centric object level semantic video operations such as product placement or obscene material removal. Experimental results show that SV-CAT is able to provide accurate object level video metadata.

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Annotation based personalized adaptation and presentation of videos for mobile applications

Cited by 7 publications

References 34 publications

Context-Aware Multimedia Content Adaptation for Mobile Web

Context-Aware Multimedia Content Adaptation for Mobile Web

Adaptive video and metadata display using multimedia documents

Fine‐granularity semantic video annotation

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