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

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Author

Ashok Mariappan and Michael Igarta and Cuneyt Taskiran and Bhavan Gandhi and Edward J. Delp

Entry type

conference

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.

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Date

2006

Editor

Reiner Creutzburg and Jarmo H. Takala and Chang Wen Chen

Journal

Multimedia on Mobile Devices II

Key alpha

mariappan:607408

Number

Pages

607408

Publisher

SPIE

Volume

6074

Affiliation

Purdue University

Publication Date

2006-01-01

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@Conference{ mariappan:607408,
	title = "A study of low-complexity tools for semantic classification of mobile video",
	author = "Ashok Mariappan and Michael Igarta and Cuneyt Taskiran and Bhavan Gandhi and Edward J. Delp",
	year = "2006",
	editor = "Reiner Creutzburg and Jarmo H. Takala and Chang Wen Chen",
	journal = "Multimedia on Mobile Devices II",
	number = "1",
	pages = "607408",
	publisher = "SPIE",
	volume = "6074",
	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.",
	affiliation = "Purdue University",
}