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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao HAL Descartesarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
HAL Descartes
Conference object . 2011
Data sources: HAL Descartes
https://doi.org/10.1109/ism.20...
Article . 2011 . Peer-reviewed
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DBLP
Conference object . 2023
Data sources: DBLP
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Characters Identification in TV Series

Authors: Maidi, Madjid; Scurtu, Veronica; Preda, Marius;

Characters Identification in TV Series

Abstract

This work aims to realize a recognition system for a software engine that will automatically generate a quiz starting from a video content and reinsert it into the video, turning thus any available foreign-language video (such as news or TV series) into a remarkable learning tool. Our system includes a face tracking application which integrates the eigen face method with a temporal tracking approach. The main part of our work is to detect and identify faces from movies and to associate specific quizzes for each recognized character. The proposed approach allows to label the detected faces and maintains face tracking along the video stream. This task is challenging since characters present significant variation in their appearance. Therefore, we employed eigen faces to reconstruct the original image from training models and we developed a new technique based on frames buffering for continuous tracking in unfavorable environment conditions. Many tests were conducted and proved that our system is able to identify multiple characters. The obtained results showed the performance and the effectiveness of the proposed method.

Country
France
Keywords

Linear discriminant analysis, Principal component analysis, Temporal tracking, Face recognition, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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