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Fusing Shape-from-Silhouette and the Sparsity Driven Detector for Camera-Based 3D Multi-Object Localization with Occlusions

Position estimation of multiple objects in a 3D environment poses a challenging task, even more so in the presence of occlusions due to infrastructure. In this paper we present a method to accurately localize up to 10 moving pedestrians by fusing the output of a Sparsity Driven Detector with volumes generated by a Shape-from-Silhouette approach. We also show how occlusion information from a 3D map of the environment can be integrated into our algorithm to further improve performance. We investigate the influence of different camera heights and image sizes on the optimization problem and demonstrate real-time capability for certain configurations. Additionally, our code is made publicly available under an open source license.1