Pregled bibliografske jedinice broj: 879472
Protecting the Privacy of Humans in Video Sequences using a Computer Vision-Based De- Identification Pipeline
Protecting the Privacy of Humans in Video Sequences using a Computer Vision-Based De- Identification Pipeline // Expert systems with applications, 87 (2017), 41-55 doi:10.1016/j.eswa.2017.05.067 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 879472 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Protecting the Privacy of Humans in Video Sequences using a Computer Vision-Based De- Identification Pipeline
Autori
Brkić, Karla ; Hrkać, Tomislav ; Kalafatić, Zoran
Izvornik
Expert systems with applications (0957-4174) 87
(2017);
41-55
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
privacy protection ; de-identification ; computer vision ; video processing
Sažetak
We propose a computer vision-based de- identification pipeline that enables automated protection of privacy of humans in video sequences through obfuscating their appearance, while preserving the naturalness and utility of the de-identified data. Our pipeline specifically addresses de-identifying soft and non-biometric features, such as clothing, hair, skin color etc., which often remain recognizable when simpler techniques such as blurring are applied. Assuming a surveillance scenario, we combine background subtraction based on Gaussian mixtures with an improved version of the GrabCut algorithm to find and segment pedestrians. De- identification is performed by altering the appearance of the segmented pedestrians through the neural art algorithm that uses the responses of a deep neural network to render the pedestrian images in a different style. Experimental evaluation is performed both by automated classification and through a user study. Results suggest that the proposed pipeline successfully de- identifies a range of hard and soft biometric and non-biometric identifiers, including face, clothing and hair.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-UIP-2013-11-1544 - Metode deidentifikacije za meke i ne-biometrijske identifikatore (DeMSI) (Hrkać, Tomislav, HRZZ ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus