Person identification system for future digital tv with intelligence

Min Cheol Hwang; Le Thanh Ha; Nam Hyeong Kim; Chun Su Park; Sung Jea Ko

doi:10.1109/TCE.2007.339528

Person identification system for future digital tv with intelligence

Min Cheol Hwang, Le Thanh Ha, Nam Hyeong Kim, Chun Su Park, Sung Jea Ko

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

Abstract

Intelligent digital TV (iDTV) is a future digital TV with intelligence which can automatically provide userpersonalized services for each audience. For the userpersonalized services, the iDTV should recognize audiences in real-time. In this paper, we define a novel structure of the iDTV and propose a real-time person identification system in the iDTV that analyzes captured images and recognizes audiences. The proposed system consists of three processing units: preprocessing for reducing computational costs of the proposed system, face detection using a statistical approach, and face recognition using Support Vector Machines (SVMs). Experimental results show that the proposed system achieves efficient performance with high recognition accuracy of 90% or higher at the speed of 15∼20 fps, which is suitable for the iDTV.

Original language	English
Pages (from-to)	218-226
Number of pages	9
Journal	IEEE Transactions on Consumer Electronics
Volume	53
Issue number	1
DOIs	https://doi.org/10.1109/TCE.2007.339528
Publication status	Published - 2007 Feb

Bibliographical note

Funding Information:
This research was supported by Seoul Future Contents Convergence (SFCC) Cluster established by Seoul Industry-Academy-Research Cooperation Project.

Keywords

Audience identification
Face detection
Face recognition
Intelligent digital TV
Personalized services

ASJC Scopus subject areas

Media Technology
Electrical and Electronic Engineering

Access to Document

10.1109/TCE.2007.339528

Cite this

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title = "Person identification system for future digital tv with intelligence",

abstract = "Intelligent digital TV (iDTV) is a future digital TV with intelligence which can automatically provide userpersonalized services for each audience. For the userpersonalized services, the iDTV should recognize audiences in real-time. In this paper, we define a novel structure of the iDTV and propose a real-time person identification system in the iDTV that analyzes captured images and recognizes audiences. The proposed system consists of three processing units: preprocessing for reducing computational costs of the proposed system, face detection using a statistical approach, and face recognition using Support Vector Machines (SVMs). Experimental results show that the proposed system achieves efficient performance with high recognition accuracy of 90% or higher at the speed of 15∼20 fps, which is suitable for the iDTV.",

keywords = "Audience identification, Face detection, Face recognition, Intelligent digital TV, Personalized services",

author = "Hwang, {Min Cheol} and Ha, {Le Thanh} and Kim, {Nam Hyeong} and Park, {Chun Su} and Ko, {Sung Jea}",

note = "Funding Information: This research was supported by Seoul Future Contents Convergence (SFCC) Cluster established by Seoul Industry-Academy-Research Cooperation Project.",

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doi = "10.1109/TCE.2007.339528",

language = "English",

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AU - Hwang, Min Cheol

AU - Ha, Le Thanh

AU - Kim, Nam Hyeong

AU - Park, Chun Su

AU - Ko, Sung Jea

N1 - Funding Information: This research was supported by Seoul Future Contents Convergence (SFCC) Cluster established by Seoul Industry-Academy-Research Cooperation Project.

PY - 2007/2

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AB - Intelligent digital TV (iDTV) is a future digital TV with intelligence which can automatically provide userpersonalized services for each audience. For the userpersonalized services, the iDTV should recognize audiences in real-time. In this paper, we define a novel structure of the iDTV and propose a real-time person identification system in the iDTV that analyzes captured images and recognizes audiences. The proposed system consists of three processing units: preprocessing for reducing computational costs of the proposed system, face detection using a statistical approach, and face recognition using Support Vector Machines (SVMs). Experimental results show that the proposed system achieves efficient performance with high recognition accuracy of 90% or higher at the speed of 15∼20 fps, which is suitable for the iDTV.

KW - Audience identification

KW - Face detection

KW - Face recognition

KW - Intelligent digital TV

KW - Personalized services

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Person identification system for future digital tv with intelligence

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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