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Paper Detail

Paper IDIFS-2.9
Paper Title End-to-end pairwise human proxemics from uncalibrated single images
Authors Pietro Morerio, Matteo Bustreo, Yiming Wang, Alessio del Bue, Istituto Italiano di Tecnologia, Italy
SessionIFS-2: Information Forensics and Security
LocationArea K
Session Time:Monday, 20 September, 15:30 - 17:00
Presentation Time:Monday, 20 September, 15:30 - 17:00
Presentation Poster
Topic Information Forensics and Security: Surveillance
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract In this work, we address the ill-posed problem of estimating pairwise metric distances between people using only a single uncalibrated image. We propose an end-to-end model, DeepProx, that takes as inputs two skeletal joints as a set of 2D image coordinates and outputs the metric distance between them. We show that an increased performance is achieved by a geometrical loss over simplified camera parameters provided at training time. Further, DeepProx achieves a remarkable generalisation over novel viewpoints through domain generalisation techniques. We validate our proposed method quantitatively and qualitatively against baselines on public datasets for which we provided groundtruth on interpersonal distances.