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Time-of-flight based scene reconstruction with a mesh processing tool for model based camera tracking

: Kahn, Svenja; Wuest, Harald; Fellner, Dieter W.

Volltext urn:nbn:de:0011-n-1345551 (800 KByte PDF)
MD5 Fingerprint: aa1148888efc30de14503d1368faf425
Erstellt am: 17.7.2010

Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
VISIGRAPP 2010, International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Proceedings. CD-ROM : Angers, France May 17 - 21, 2010
Porto: INSTICC Press, 2010
ISBN: 978-989-674-028-3
International Conference on Computer Vision Theory and Applications (VISAPP) <5, 2010, Angers>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IGD ()
3D reconstruction; sensor fusion; augmented reality (AR); time-of-flight camera (TOF camera); camera tracking

The most challenging algorithmical task for markerless Augmented Reality applications is the robust estimation of the camera pose. With a given 3D model of a scene the camera pose can be estimated via model-based camera tracking without the need to manipulate the scene with fiducial markers. Up to now, the bottleneck of model-based camera tracking is the availability of such a 3D model. Recently time-of-flight cameras were developed which acquire depth images in real time. With a sensor fusion approach combining the color data of a 2D color camera and the 3D measurements of a time-of-flight camera we acquire a textured 3D model of a scene. We propose a semi-manual reconstruction step in which the alignment of several submeshes with a mesh processing tool is supervised by the user to ensure a correct alignment. The evaluation of our approach shows its applicability for reconstructing a 3D model which is suitable for model-based camera tracking even for objects which are difficult to measure reliably with a time-of-flight camera due to their demanding surface characteristics.