Naslov
An Online Multi-Face Tracker for Unconstrained Videos

Autori
Marčetić, Darijan ; Ribarić, Slobodan ;

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

Izvornik
Proceedings SITIS 2018 / - New York (NY) : IEEE Computer Society Conference Publishing Services, 2018, 159-165

ISBN
978-1-5386-9385-8

Skup
14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2018)

Mjesto i datum
Las Palmas de Gran Canaria, Španjolska, 26.11.2018. - 29.11.2018

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Multi-face tracking, Tracking by detection, Face identity label assignment

Sažetak
This paper presents a system for online multi-face tracking in unconstrained videos. Different shooting angles, strong illumination changes, abrupt motion and face pose changes are the main characteristics of these videos. The proposed online multi-face tracking system combines deep convolutional neural network face detection, multiple instances of a tracker based on discriminative scale and space correlation filters, shot change detection, tracking failure detection, tracklet generation, and ResNet-based face identity label assignment. The system is tested on a dataset of YouTube music videos which is characterised by video sequences with great visual differences caused by face appearance variations (changes in pose, size, makeup, and illumination), and/or rapid camera motion. The results of the experiment expressed by MOTA, MOTP and IDS metrics are given and compared with state-of-the-art multi-target trackers.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA