Naslov
De-identifying people in videos using neural art

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

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proc. Image Processing Theory Tools and Applications (IPTA), 2016 6th International Conference on / - : Institute of Electrical and Electronics Engineers (IEEE), 2016, 1-6

ISBN
978-1-4673-8910-5

Skup
2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)

Mjesto i datum
Oulu, Finska, 12.12.2016. - 15.12.2016

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
de-identification, neural art, privacy protection, computer vision

Sažetak
We propose a computer vision-based de- identification pipeline that enables automated segmentation of humans in videos and effective protection of their identities. Due to the ubiquity of video surveillance, many jurisdictions implement strict regulations for the protection of personal data in publicly collected video sequences, requiring the data to be de-identified. However, soft biometric and non-biometric features like clothing, hair color, personal items, skin marks, etc., are often overlooked in the process. Assuming a surveillance scenario, we combine GMM-based background subtraction with an improved version of the GrabCut algorithm to find and segment pedestrians. We use the responses of a deep neural network to de-identify soft and non- biometric features through style mixing with images of other pedestrians. Our method produces de-identified versions of the input frames while preserving the naturalness and utility of the de-identified data.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA