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Action recognition in the longwave infrared and the visible spectrum using Hough forests

: Hilsenbeck, Barbara; Münch, David; Grosselfinger, Ann-Kristin; Hübner, Wolfgang; Arens, Michael

Postprint urn:nbn:de:0011-n-4264547 (2.2 MByte PDF)
MD5 Fingerprint: fc023b531206f4e20bde863ea77ec6e8
Erstellt am: 22.12.2016

Kankanhalli, M.S. ; Institute of Electrical and Electronics Engineers -IEEE-:
ISM 2016, IEEE International Symposium on Multimedia. Proceedings : 11-13 December 2016, San Jose, California
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-5090-4571-6
ISBN: 978-1-5090-4572-3 (Print)
ISBN: 978-1-5090-4570-9
International Symposium on Multimedia (ISM) <18, 2016, San Jose/Calif.>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Action recognition in surveillance systems has to work 24/7 under all kinds of weather and lighting conditions. Towards this end, most action recognition systems only work in the visible spectrum which limits their general usage to daytime applications. In this work Hough forests are applied to the longwave infrared spectrum which can capture humans both in the dark and in daylight. Further, Integral Channel Features which have shown promising results in the spatial domain are applied to the spatio-temporal domain and are incorporated into the Hough forest approach. This approach is evaluated on a new outdoor dataset containing different violent and non-violent actions recorded in the visible and infrared spectrum. It is further shown that for the visible spectrum the proposed approach achieves state-of-the-art results on the KTH and i3DPost dataset.