Pregled bibliografske jedinice broj: 712902
Person De-Identification in Activity Videos
Person De-Identification in Activity Videos // BiForD - BIOMETRICS & FORENSICS & DE- IDENTIFICATION AND PRIVACY PROTECTION / Slobodan Ribaric (ur.).
Opatija: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2014. str. 75-80 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 712902 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Person De-Identification in Activity Videos
Autori
Ivašić-Kos, Marina ; Iosifidis, Alexandros ; Tefas, Anastasios ; Pitas, Ioannis
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
BiForD - BIOMETRICS & FORENSICS & DE- IDENTIFICATION AND PRIVACY PROTECTION
/ Slobodan Ribaric - Opatija : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2014, 75-80
Skup
BiForD, Special Session on Biometrics, Forensics, De-identification and Privacy Protection
Mjesto i datum
Opatija, Hrvatska, 29.05.2014. - 30.05.2014
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
de-identification of human body silhouette; action recognition; Gaussian filter
Sažetak
Person identification based on gait recognition has been extensively studied in the last two decades, while information appearing in different action types (like bend) has been recently exploited to this end. However, in most application scenarios it is sufficient to recognize the performed activity, whereas the iD of persons performing activities is not important. since the same human body representations, e.g., body silhouettes, can be employed for both tasks, there is a need to automatically create privacy preserving representations. We have applied 2D gaussian filtering to obfuscate the human body silhouettes that implicate information about the person iD. We have experimentally showed how the use of filtering affects the person identification and action recognition performance in different camera setups formed by an arbitrary number of cameras. in addition, the discriminative ability of different activities is examined and discussed in order to detect cases in which it is possible to apply gaussian filter with a greater variance.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet informatike i digitalnih tehnologija, Rijeka
Profili:
Marina Ivašić Kos
(autor)