Naslov
Image Representations on a Budget: Traffic Scene Classification in a Restricted Bandwidth Scenario

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

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

Izvornik
Proceedings of 2014 IEEE Intelligent Vehicles Symposium (IV) / - , 2014, 845-852

ISBN
978-1-4799-3637-3

Skup
2014 IEEE Intelligent Vehicles Symposium (IV)

Mjesto i datum
Dearborn (MI), Sjedinjene Američke Države, 08.07.2014. - 11.07.2014

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
traffic scene recognition; representation budget; fleet management; image representations

Sažetak
Modern fleet management systems typically monitor the status of hundreds of vehicles by relying on GPS and other simple sensors. Such systems experience significant problems in cases of GPS glitches as well as in areas without GPS coverage. Additionally, when the tracked vehicle is stationary, they cannot discriminate between traffic jams, service stations, parking lots, serious accidents and other interesting scenarios. We propose to alleviate these problems by augmenting the GPS information with a short descriptor of an image captured by an on-board camera. The descriptor allows the server to recognize various scene types by image classification and to subsequently implement suitable business policies. Due to restricted bandwidth we focus on finding a compact image representation that would still allow reliable classification. We therefore consider several state-of-the-art descriptors under tight representation budgets of 512, 256, 128 and 64 components, and evaluate classification performance on a novel image dataset specifically crafted for fleet management applications. Experimental results indicate fair performance even with very short descriptor sizes and encourage further research in the field.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

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