Ghost pruning for people localization in overlapping multicamera systems

In this paper, we propose a novel ghost pruning technique for multicamera people localization in overlapping scenarios. First, synergy map is obtained from multiplanar projections across multiple overlapping cameras. Second, occupancy map is generated by back projection from the synergy map across various image layers. This back projected occupancy map is combined with constraints to remove ghosts. The novelty of this paper is the introduction of an intuitive ghost pruning technique, which does not require any temporal information. Experiments on a sequence of the PETS 2009 dataset show significant reduction in the number of ghosts. The purpose and novelty of this paper is focused to the ghost pruning module but detection metrics show results comparable to those of the complete, state-of-the-art multicamera object detection systems.