Fundamentals of digital image processing
Fundamentals of digital image processing
Shape measures for content based image retrieval: a comparison
Information Processing and Management: an International Journal
A probabilistic framework for semantic video indexing, filtering,and retrieval
IEEE Transactions on Multimedia
Techniques and data structures for efficient multimedia retrieval based on similarity
IEEE Transactions on Multimedia
Color image retrieval based on hidden Markov models
IEEE Transactions on Image Processing
An integrated approach for content-based video object segmentation and retrieval
IEEE Transactions on Circuits and Systems for Video Technology
A semantic event-detection approach and its application to detecting hunts in wildlife video
IEEE Transactions on Circuits and Systems for Video Technology
Fast and automatic video object segmentation and tracking for content-based applications
IEEE Transactions on Circuits and Systems for Video Technology
Object-based video abstraction for video surveillance systems
IEEE Transactions on Circuits and Systems for Video Technology
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This paper presents a novel scheme of object-based video indexing and retrieval based on video abstraction and semantic event modeling. The proposed algorithm consists of three major steps; Video Object (VO) extraction, object-based video abstraction and statistical modeling of semantic features. Semantic feature modeling scheme is based on temporal variation of low-level features in object area between adjacent frames of video sequence. Each semantic feature is represented by a Hidden Markov Model (HMM) which characterizes the temporal nature of VO with various combinations of object features. The experimental results demonstrate the effective performance of the proposed approach.