Foreground object detection in highly dynamic scenes using saliency

Kai-Hsiang Lin, Pooya Khorrami, Jiangping Wang, Mark Hasegawa-Johnson, Thomas S. Huang
2014 2014 IEEE International Conference on Image Processing (ICIP)  
In this paper, we propose a novel saliency-based algorithm to detect foreground regions in highly dynamic scenes. We first convert input video frames to multiple patch-based feature maps. Then, we apply temporal saliency analysis to the pixels of each feature map. For each temporal set of co-located pixels, the feature distance of a point from its k th nearest neighbor is used to compute the temporal saliency. By computing and combing temporal saliency maps of different features, we obtain
more » ... round likelihood maps. A simple segmentation method based on adaptive thresholding is applied to detect the foreground objects. We test our algorithm on images sequences of dynamic scenes, including public datasets and a new challenging wildlife dataset we constructed. The experimental results demonstrate the proposed algorithm achieves state-of-the-art results.
doi:10.1109/icip.2014.7025224 dblp:conf/icip/LinKWHH14 fatcat:fxc4tvn5zbgtxnxkdax76jsu2i