Robust Automatic Face Recognition

Roshan Kavuri; Sani Kommu Vasavi

Robust Automatic Face Recognition

Roshan Kavuri * §

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Sani Kommu Vasavi

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rsravani

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§ Department of Information Technology J.B.Instute of ...

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Abstract

The crux of the character identification problem is to exploit the relations between videos and the associated texts in order to label the faces of characters with names. It has similarities to identifying faces in news videos. However, in news videos, candidate names for the faces are available from the simultaneously appearing captions or local transcripts. While in TV and movies, the names of characters are seldom directly shown in the subtitle or closed caption, and script/screenplay containing character names has no time stamps to align to the video. According to the utilized textual cues, we roughly divide the existing movie character identification methods into three categories In this Robust Face-Name Graph Matching for Movie Character Identification is used to detect the face of movie characters and the Proposed system is taking the minimum time to detect the face. In this one we can do it in a minute process.

References

4 Cites in Article

Reference Format

Johannes Stallkamp,Hazim Ekenel,Rainer Stiefelhagen (2007). Video-based Face Recognition on Real-World Data.
J Yang,A Hauptmann (2005). multiple instance learning for labelling faces in broad casting news video.
O Arandjelovic,R Cippolla (2006). automatic cast listing in feature-length films with anisotropic manifold space.
Deva Ramanan,Simon Baker,Sham Kakade (2007). Leveraging archival video for building face datasets.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Roshan Kavuri, Sani Kommu Vasavi, rsravani. 1970. "Robust Automatic Face Recognition". Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F4).

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GJCST Volume 13 Issue F4

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

face recognition biometrics image processing Pattern recognition pixels psychophysics

Classification

GJCST-F Classification I.4.8

Submission ReceivedDecember 8, 2012
Peer Review Double Blind
Handling Editor
Accepted January 3, 2013
Published January 15, 2013

Version of record

v1.2

Language

English

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Article Matrices

Total Score: 143

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Roshan Kavuri, Sani Kommu Vasavi , Ramisety Sravani (PhD/Dr. count: 0)

View Count (all-time): 421

Total Views (Real + Logic): 10369

Total Downloads (simulated): 670

Publish Date: 2013 01, Tue

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Total Views: 10.4K

Total Downloads: 670

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