Robust Automatic Face Recognition

1
Roshan Kavuri
Roshan Kavuri
2
Sani Kommu Vasavi
Sani Kommu Vasavi
3
Ramisety Sravani
Ramisety Sravani
1 Department of Information Technology J.B.Instute of Engineering & Technology

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GJCST Volume 13 Issue F4

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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.

4 Cites in Articles

References

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

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.

Roshan Kavuri. 1970. \u201cRobust Automatic Face Recognition\u201d. 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
Pg. 21- 25
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Crossref Journal DOI 10.17406/gjcst

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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.

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.

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Robust Automatic Face Recognition

Roshan Kavuri
Roshan Kavuri Department of Information Technology J.B.Instute of Engineering & Technology
Sani Kommu Vasavi
Sani Kommu Vasavi
Ramisety Sravani
Ramisety Sravani

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