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Classifying Traffic Scenes Using The GIST Image Descriptor (CROSBI ID 602492)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Sikirić, Ivan ; Brkić, Karla ; Šegvić, Siniša Classifying Traffic Scenes Using The GIST Image Descriptor // CCVW 2013 Proceedings of the Croatian Computer Vision Workshop / Lončarić, Sven ; Šegvić, Siniša (ur.). Zagreb: Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu, 2013. str. 1-6

Podaci o odgovornosti

Sikirić, Ivan ; Brkić, Karla ; Šegvić, Siniša

engleski

Classifying Traffic Scenes Using The GIST Image Descriptor

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.

computer vision

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Podaci o prilogu

1-6.

2013.

objavljeno

Podaci o matičnoj publikaciji

CCVW 2013 Proceedings of the Croatian Computer Vision Workshop

Lončarić, Sven ; Šegvić, Siniša

Zagreb: Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu

1849-1227

Podaci o skupu

Croatian Computer Vision Workshop

predavanje

19.09.2013-19.09.2013

Zagreb, Hrvatska

Povezanost rada

Računarstvo

Poveznice