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2002

Factor graph framework for semantic video indexing

10 years 10 months ago
Factor graph framework for semantic video indexing
Video query by semantic keywords is one of the most challenging research issues in video data management. To go beyond low-level similarity and access video data content by semantics, we need to bridge the gap between the low-level representation and high-level semantics. This is a difficult multimedia understanding problem. We formulate this problem as a probabilistic pattern-recognition problem for modeling semantics in terms of concepts and context. To map low-level features to high-level semantics, we propose probabilistic multimedia objects (multijects). Examples of multijects in movies include explosion, mountain, beach, outdoor, music, etc. Semantic concepts in videos interact and appear in context. To model this interaction explicitly, we propose a network of multijects (multinet). To model the multinet computationally, we propose a factor graph framework which can enforce spatio-temporal constraints. Using probabilistic models for multijects, rocks, sky, snow, water-body, and ...
Milind R. Naphade, Igor Kozintsev, Thomas S. Huang
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where TCSV
Authors Milind R. Naphade, Igor Kozintsev, Thomas S. Huang
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