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Publications in Scientific Journals:

S. Ghuffar, N. Brosch, N. Pfeifer, M. Gelautz:
"Motion estimation and segmentation in depth and intensity videos";
Integrated Computer-Aided Engineering, 21 (2014), 3; 203 - 218.



English abstract:
This paper investigates motion estimation and segmentation of independently moving objects in video sequences that contain depth and intensity information, such as videos captured by a Time of Flight camera. Specifically, we present a motion estimation algorithm which is based on integration of depth and intensity data. The resulting motion information is used to derive long-term point trajectories. A segmentation technique groups the trajectories according to their motion and depth similarity into spatio-temporal segments. Quantitative and qualitative analysis of synthetic and real world videos verify the proposed motion estimation and segmentation approach. The proposed framework extracts independently moving objects from videos recorded by a Time of Flight camera.

German abstract:
This paper investigates motion estimation and segmentation of independently moving objects in video sequences that contain depth and intensity information, such as videos captured by a Time of Flight camera. Specifically, we present a motion estimation algorithm which is based on integration of depth and intensity data. The resulting motion information is used to derive long-term point trajectories. A segmentation technique groups the trajectories according to their motion and depth similarity into spatio-temporal segments. Quantitative and qualitative analysis of synthetic and real world videos verify the proposed motion estimation and segmentation approach. The proposed framework extracts independently moving objects from videos recorded by a Time of Flight camera.

Keywords:
ToF camera, range flow, optical flow, motion estimation, segmentation


"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.3233/ICA-130456

Electronic version of the publication:
http://iospress.metapress.com/content/d3w46m66j418548r/


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