BIOLOGICALLY INSPIRED ATTENTIVE MOTION ANALYSIS FOR VIDEO SURVEILLANCE
Florian Raudies, Heiko Neumann · 2008
Abstract: Recently proposed algorithms in the field of vision-based video surveillance are build upon directionally con-sistent flow (Wixson and Hansen, 1999; Tian and Hampapur, 2005), or statistics of foreground and back-ground (Ren et al., 2003; Zhang et al., 2007). Here, we present a novel approach which utilizes an attention mechanism to focus processing on (highly) suspicious image regions. The attention signal is generated through temporal integration of localized image features from monocular image sequences. This approach incorpo-rates biologically inspired mechanisms, for feature extraction and spatio-temporal grouping. We compare our approach with an existing method for the task of video surveillance (Tian and Hampapur, 2005) with a re-ceiver operator characteristic (ROC) analysis. In conclusion our model is shown to yield results which are comparable with existing approaches. 1