8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      3D model silhouette-based tracking in depth images for puppet suit dynamic video-mapping

      Preprint
      , ,

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Video-mapping is the process of coherent video-projection of images, animations or movies on static objects or buildings for shows. This paper focuses on the dynamic video-mapping of the suit of a puppet being moved by its puppeteer on the theater stage. This may allow changing the costume dynamically and simulate light interaction and more. Contrary to common video-mapping, the image warping cannot be done once, offline, before the show. It must be done in real-time, and considering a non-flat projection surface, so that the video-projected suit always maps perfectly the puppet, automatically. Hence, we propose a new visual tracking method of articulated object, for the puppet tracking, exploiting the silhouette of a 3D model of it, in the depth images of a Kinect v2. Then, considering the precise calibration between the latter and the video-projector, that we propose, coherent dynamic video-mapping is made possible as the presented results show.

          Related collections

          Most cited references8

          • Record: found
          • Abstract: not found
          • Article: not found

          Monocular Model-Based 3D Tracking of Rigid Objects: A Survey

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            ViSP for visual servoing: a generic software platform with a wide class of robot control skills

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              A maximum likelihood framework for determining moving edges

                Bookmark

                Author and article information

                Journal
                09 October 2018
                Article
                1810.03956
                7ba77f85-a35c-406d-9317-b952607c03b3

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                8 pages, 8 figures
                cs.CV

                Computer vision & Pattern recognition
                Computer vision & Pattern recognition

                Comments

                Comment on this article