کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
536687 870607 2007 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Temporal Bayesian Network based contextual framework for structured information mining
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Temporal Bayesian Network based contextual framework for structured information mining
چکیده انگلیسی

Specific domains in video data contain rich temporal structures that help in classification process. In this paper, we exploit the temporal structure to characterize video sequence data into different classes. We propose the following perceptual features: Time-to-Collision, shot length and transition, and temporal motion activity. Using these perceptual features, several video classes are characterized leading to formation of high-level sequence classification. Resulting high-level queries are more easily mapped onto the perceptual features enabling better accessibility of content-based retrieval systems. Temporal fusion of the perceptual features forms higher-level structures, which can be effectively tackled using the Dynamic Bayesian Networks. The Networks allow the power of statistical inference and learning to be combined with the temporal and contextual knowledge of the problem. The modeling and experimental results are presented for a number of key applications, like sequence identification, extracting highlights for sports, and parsing a news program.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 28, Issue 14, 15 October 2007, Pages 1873–1884
نویسندگان
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