Towards Neural Art-based Face De-identification in Video Data (CROSBI ID 638979)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
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