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Proceedings Paper

A study of low-complexity tools for semantic classification of mobile video
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Paper Abstract

With the proliferation of cameras in handheld devices that allows users to capture still images and videos, providing users with software tools to efficiently manage multimedia content has become essential. In many cases users desire to organize their personal media content using high-level semantic labels. In this paper we will describe low-complexity algorithms that can be used to derive semantic labels, such as "indoor/outdoor," "face/not face," and "motion/not motion" for mobile video sequences. We will also describe a method for summarizing mobile video sequences. We demonstrate the classification performance of the methods and their computational complexity using a typical processor used in many mobile terminals.

Paper Details

Date Published: 10 February 2006
PDF: 12 pages
Proc. SPIE 6074, Multimedia on Mobile Devices II, 607408 (10 February 2006); doi: 10.1117/12.643246
Show Author Affiliations
Ashok Mariappan, Purdue Univ. (United States)
Michael Igarta, Purdue Univ. (United States)
Cuneyt Taskiran, Motorola Labs. (United States)
Bhavan Gandhi, Motorola Labs. (United States)
Edward J. Delp, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 6074:
Multimedia on Mobile Devices II
Reiner Creutzburg; Jarmo H. Takala; Chang Wen Chen, Editor(s)

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