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Joint Vanishing Point Extraction and Tracking

Till Kroeger, Dengxin Dai, Luc Van Gool
Computer Vision and Pattern Recognition


We present a novel vanishing point (VP) detection and tracking algorithm for calibrated monocular image sequences. Previous VP detection and tracking methods usually assume known camera poses for all frames or detect and track separately. We advance the state-of-the-art by combining VP extraction on a Gaussian sphere with recent advances in multi-target tracking on probabilistic occupancy?elds. ThesolutionisobtainedbysolvingaLinear Program (LP). This enables the joint detection and tracking of multiple VPs over sequences. Unlike existing works we do not need known camera poses, and at the same time avoiddetectingandtrackinginseparatesteps. WealsoproposeanextensiontoenforceVPorthogonality. Weaugment anexistingvideodatasetconsistingof48monocularvideos with multiple annotated VPs in 14448 frames for evaluation. Although the method is designed for unknown camera poses,itisalsohelpfulinscenarioswithknownposes,since a multi-frame approach in VP detection helps to regularize in frames with weak VP line support

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  author = {Till Kroeger and Dengxin Dai and Luc Van Gool},
  title = {Joint Vanishing Point Extraction and Tracking},
  booktitle = {Computer Vision and Pattern Recognition},
  year = {2015},
  keywords = {}