Naslov
Classifying Traffic Scenes Using The GIST Image Descriptor

Autori
Sikirić, Ivan ; Brkić, Karla ; Šegvić, Siniša

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

Izvornik
CCVW 2013 Proceedings of the Croatian Computer Vision Workshop / Lončarić, Sven ; Šegvić, Siniša - Zagreb : Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu, 2013, 1-6

Skup
Croatian Computer Vision Workshop

Mjesto i datum
Zagreb, Hrvatska, 19.09.2013

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
computer vision

Sažetak
This paper proposes combining spatio-temporal ap- pearance (STA) descriptors with optical flow for human action recognition. The STA descriptors are local histogram-based descriptors of space-time, suitable for building a partial rep- resentation of arbitrary spatio-temporal phenomena. Because of the possibility of iterative refinement, they are interesting in the context of online human action recognition. We investigate the use of dense optical flow as the image function of the STA descriptor for human action recognition, using two different algorithms for computing the flow: the Farnebäck algorithm and the TV- L1 algorithm. We provide a detailed analysis of the influencing optical flow algorithm parameters on the produced optical flow fields. An extensive experimental validation of optical flow-based STA descriptors in human action recognition is performed on the KTH human action dataset. The encouraging experimental results suggest the potential of our approach in online human action recognition.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

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