Automatic partitioning of full-motion video
Multimedia Systems
Joint Haar-like Features for Face Detection
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
A bootstrapping approach for identifying stakeholders in public-comment corpora
dg.o '07 Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains
LocalSavvy: aggregating local points of view about news issues
Proceedings of the first international workshop on Location and the web
Identifying news videos' ideological perspectives using emphatic patterns of visual concepts
MM '09 Proceedings of the 17th ACM international conference on Multimedia
ASIFT: A New Framework for Fully Affine Invariant Image Comparison
SIAM Journal on Imaging Sciences
Credibility-oriented ranking of multimedia news based on a material-opinion model
WAIM'11 Proceedings of the 12th international conference on Web-age information management
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We are studying contents analysis of multimedia news as a solution to the issue of bias, which multimedia news, as a reflection of the real world, is also facing. For the contents analysis, we use a stakeholder model representing descriptions of different stakeholders, which are defined as the main participants in an event. In this paper, we propose a method of detecting stakeholders as the core component of the stakeholder-oriented analysis. In our work, a stakeholder is assumed to appear in the video clips and be mentioned in the closed captions frequently. Given a series of video clips and their closed captions reporting the same event, we extract stakeholder candidates from both textual and visual descriptions. After that, we calculate the degree of exposure for each candidate to identify stakeholders. We also present experimental results that validate our method.