VANISHING POINT-BASED LINE SAMPLING FOR EFFICIENT AXIS-BASED PEOPLE LOCALIZATION

Abstract

In this paper, we propose an efficient people localization approach using multiple cameras based on axial representations of foreground regions. Unlike many previous methods that need to project all foreground pixels of all views to multiple reference planes via homography, we instead apply vanishing point-based line sampling to reduce the large amount of pixel processing so that computational efficiency can be greatly enhanced. Experimental simulations show that the proposed approach is more than 40 times faster than the compared, pixel-based localization method on average, without sacrificing the localization accuracy.