Temporal saliency for fast motion detection

Authors:
Hamed Rezazadegan Tavakoli;Esa Rahtu;Janne Heikkilä
Affiliations:
Center for Machine Vision Research, University of Oulu, Oulu, Finland;Center for Machine Vision Research, University of Oulu, Oulu, Finland;Center for Machine Vision Research, University of Oulu, Oulu, Finland
Venue:
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume Part I
Year:
2012

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Abstract

This paper presents a novel saliency detection method and apply it to motion detection. Detection of salient regions in videos or images can reduce the computation power which is needed for complicated tasks such as object recognition. It can also help us to preserve important information in tasks like video compression. Recent advances have given birth to biologically motivated approaches for saliency detection. We perform salience estimation by measuring the change in pixel's intensity value within a temporal interval while performing a filtering step via principal component analysis that is intended to suppress noise. We applied the method to Background Models Challenge (BMC) video data set. Experiments show that the proposed method is apt and accurate. Additionally, the method is fast to compute.