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Mining for video production invariants to measure style similarity
Author(s) -
Haidar Siba,
Joly Philippe,
Chebaro Bilal
Publication year - 2006
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20158
Subject(s) - similarity measure , invariant (physics) , similarity (geometry) , computer science , measure (data warehouse) , style (visual arts) , set (abstract data type) , similitude , pattern recognition (psychology) , artificial intelligence , algorithm , data mining , mathematics , image (mathematics) , programming language , geography , archaeology , mathematical physics
This article focuses on video document comparison using audiovisual production invariants (API). API are characterized by invariant segments obtained on a set of low‐level features. We propose an algorithm to detect production invariants throughout a collection of audiovisual documents. The algorithm runs on low‐level features, considered as time series, and extracts invariant segments using a one‐dimensional morphological envelop comparison. Then, based on the extracted results, we define a style similarity measure between two video documents. A derivative pseudo distance is also proposed. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 747–763, 2006.