This work describes a visual markerless real-time tracking system for augmented reality applications. The system uses a firewire camera with a fisheye lens mounted at 10 fps. Visual tracking of 3D scene points is performed simultaneously with 3D camera pose estimation without any prior scene knowledge. All visual-geometric data is acquired using a structure-from-motion approach. The lens selection was driven by research results that show the superiority of a fisheye lens to a standard perspective lens for this approach. 2D features in the hemispherical image are tracked using a 2D point tracker. Based on the feature tracks, 3D camera ego-motion and 3D features are estimated.

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Abstract In this paper we present a novel approach for interactive rendering of virtual views from real image sequences.Combining the concepts of light fields, depth‐compensated image warping and view dependent texture mapping,this plenoptic modeling approach can handle large and complex scenes. A portable, handheld multi‐camera systemhas been developed that allows to record multiple image streams by simply walking around the scene. Theseimage streams are automatically calibrated and depth maps for all views are generated as input to the renderingstage. For rendering a view dependent warping surface is constructed on the fly and depth‐compensated imageinterpolation is applied with view‐dependent texture mapping. Rendering quality is scalable to allow fast previewand to achieve high‐end quality with the same approach. The system can handle large and geometrically complexscenes with hundreds of real images at interactive rates. Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Viewing algorithms, I.4.1[Image Processing and Computer Vision]: Digitization and Image Capture, I.4.8 [Image Processing and ComputerVision]: Scene Analysis