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Title: Video representation and retrieval using spatio-temporal descriptors and region relations
Authors: Doulamis, Anastasios D. 
Kosmopoulos, Dimitrios 
Chatzis, Sotirios P. 
Doulamis, Anastasios D. 
Kosmopoulos, Dimitrios 
Keywords: Computer science
Neural networks
Graph theory
Problem solving
Machine learning
Issue Date: 2006
Publisher: Springer
Source: Artificial neural networks – ICANN 2006: 16th international conference, Athens, Greece, September 10-14, 2006. Proceedings, Part II, Pages 94-103
Abstract: This paper describes a novel methodology for video summarization and representation. The video shots are processed in space-time as 3D volumes of pixels. Pixel regions with consistent color and motion properties are extracted from these 3D volumes by a space-time segmentation technique based on a novel machine learning algorithm. Each region is then described by a high-dimensional point whose components represent the average position, motion velocity and color of the region. Subsequently, the spatio-temporal relations of the regions are deduced and a concise, graph-based description of them is generated. This graph-based description of the video shot's content, along with the region centroids, comprises a concise yet powerful description of the video-shot and is used for retrieval applications. The retrieval problem is formulated as an inexact graph matching problem between the data video shots and the query input which is also a video segment. Experimental results on action recognition and video retrieval are illustrated and discussed
ISBN: 978-3-540-38871-5 (print)
978-3-540-38873-9 (online)
DOI: 10.1007/11840930_10
Rights: © Springer-Verlag Berlin Heidelberg 2006
Appears in Collections:Κεφάλαια βιβλίων/Book chapters

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