A multi-resolution approach for massively-parallel hardware-friendly optical flow estimation
Journal of Visual Communication and Image Representation
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In this paper, we present a new approach to count thenumber of people that cross a counting line from monocularvideo images. The proposed approach accumulates imageslices and estimates the optical flow on them. Then, it performsan online blob detection on these slices in order toextract the crossing persons. The number of persons associatedto each blob is determined using a linear regressionmodel applied to blob features which are the position, velocity,orientation and size. The proposed approach is validatedon several datasets captured using either a verticaloverhead or an oblique mounted camera. The real-time performanceand the high counting accuracy of this approachin indoor and outdoor environments are also demonstrated.