Talks and Poster Presentations (with Proceedings-Entry):

C. Toth, D. Grejner-Brzezinska, A. Kealy, G. Retscher:
"Personal Navigation and Indoor Mapping: Performance Characterization of Kinect Sensor-based Trajectory Recovery";
Talk: XXV International FIG Congress, Kuala Lumpur, Malaysia (invited); 2014-06-16 - 2014-06-21; in: "XXV International FIG Congress", (2014), ISBN: 978-87-92853-21-9; Paper ID 7172, 12 pages.

English abstract:
The Microsoft KinectTM sensor has gained popularity in a large number of applications beyond its intended original design of being a 3D human interface device, including indoor mapping and navigation of pushcart and backpack sensor platforms. Indoor mapping and personal navigation systems are generally based on the multisensory integration model, as currently no sensor itself can provide a robust and accurate navigation solution. To assess the error budget as well as to support the design of such systems, the individual sensor error budgets should be known (estimated). In this paper, a performance analysis of the Kinect sensor is provided based on a series of indoor tests, where sufficient control, based on UWB trajectory reference, was available. The main goal of the study is to assess the trajectory reconstruction performance from Kinect imagery only, using widely available mainstream computer vision methods to process 2D and 3D image sequences. Test data was acquired by the Kinect sensor mounted on the top of a pedestrian backpack navigation prototype in forward looking orientation with a clear field of view, and a user walked a hallway loop in several patterns. The results were evaluated based on a UWB-based reference solution.

KinectTM sensor, indoor navigation, indoor mapping

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.