Napredna pretraga

Pregled bibliografske jedinice broj: 719788

Person De-identification in Activity Videos

Ivašić-Kos, Marina; Iosifidis, Alexandros; Tefas, Anastasios; Pitas, Ioannis
Person De-identification in Activity Videos // BiForD - Biometrics & Forensics & De- identification and Privacy Protection / Slobodan Ribarić (ur.).
Rijeka: MIPRO, 2014. str. 75-80 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)

Person De-identification in Activity Videos

Ivašić-Kos, Marina ; Iosifidis, Alexandros ; Tefas, Anastasios ; Pitas, Ioannis

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

BiForD - Biometrics & Forensics & De- identification and Privacy Protection / Slobodan Ribarić - Rijeka : MIPRO, 2014, 75-80


37th International IEEE Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2014

Mjesto i datum
Opatija, Hrvatska, 26-30.05.2014.

Vrsta sudjelovanja

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
De-identification of human body silhouette; action recognition; Gaussian filter

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

Znanstvena područja


Projekt / tema
318-0361935-0852 - Govorne tehnologije (Ivo Ipšić, )

Sveučilište u Rijeci - Odjel za informatiku

Autor s matičnim brojem:
Marina Ivašić-Kos, (229324)