Abstract

We address the problem of key frame extraction in the compressed domain that is of great importance in content-based system applications. A novel MPEG-7 motion activity descriptor is discussed that is a combination of temporal and spatial descriptors. These descriptors represent both temporal motion intensity as well as spatial distribution of motion activity. It is assumed that the apriori information about the shot boundaries is available. The temporal descriptors are obtained by classifying the shots into five different intensity levels based on fuzzy membership functions. A high value of intensity indicates high activity and a low value of intensity indicates low activity. The spatial descriptors are obtained using motion vectors. The individual frames are characterized into spatial regions depending on the change in motion activity between successive frames. The main motivation behind this approach is to pick those frames as key frames that have maximum centralized spatial activity and high motion intensity. The motion intensity and spatial distribution are then fed to a neural network that decides the key frames based on maximum temporal activity and centralized spatial distribution. Results illustrate that the proposed approach is computationally less intensive once the network is trained and works much better than selecting the first frame and middle frame of the shot as key frame for a wide range of video sequences.

Publication Date

11-9-2003

Comments

"Key frame extraction using MPEG-7 motion descriptors," Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, 2003. The Institute of Electrical and Electronics Engineers. Held 9-12 November 2003. ©2003 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.ISBN:0-7803-8104-1Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type

Article

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)

Campus

RIT – Main Campus

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