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Towards Neural Art-based Face De-identification in Video Data (CROSBI ID 638979)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Brkić, Karla ; Hrkać, Tomislav ; Sikirić, Ivan ; Kalafatić, Zoran Towards Neural Art-based Face De-identification in Video Data // Sensing, Processing and Learning for Intelligent Machines (SPLINE), 2016 First International Workshop on. Aaalborg: Institute of Electrical and Electronics Engineers (IEEE), 2016. str. 11-15

Podaci o odgovornosti

Brkić, Karla ; Hrkać, Tomislav ; Sikirić, Ivan ; Kalafatić, Zoran

engleski

Towards Neural Art-based Face De-identification in Video Data

We propose a computer vision-based pipeline that enables altering the appearance of faces in videos. Assuming a surveillance scenario, we combine GMM-based background subtraction with an improved version of the GrabCut algorithm to find and segment pedestrians. Independently, we detect faces using a standard face detector. We apply the neural art algorithm, utilizing the responses of a deep neural network to obfuscate the detected faces through style mixing with reference images. The altered faces are combined with the original frames using the extracted pedestrian silhouettes as a guideline. Experimental evaluation indicates that our method has potential in producing de-identified versions of the input frames while preserving the utility of the de-identified data.

deep learning; neural art; face de-identification

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Podaci o prilogu

11-15.

2016.

objavljeno

Podaci o matičnoj publikaciji

Sensing, Processing and Learning for Intelligent Machines (SPLINE), 2016 First International Workshop on

Aaalborg: Institute of Electrical and Electronics Engineers (IEEE)

978-1-4673-8917-4

Podaci o skupu

First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE)

predavanje

06.07.2016-08.07.2016

Aalborg, Danska

Povezanost rada

Računarstvo