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Using trajectories derived by dense optical flows as a spatial component in background subtraction

 
: Radolko, Martin; Farhadifard, Fahimeh

:
Postprint urn:nbn:de:0011-n-4450154 (7.9 MByte PDF)
MD5 Fingerprint: 19462cd47fa77b15bf2bf9c7dafc8cb6
Created on: 20.9.2017

Fulltext (PDF; )

Skala, V.:
24th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2016. Full Papers Proceedings : Plzen, Czech Republic, May 30 - June 3, 2016
Brno: Vaclav Skala - Union Agency, 2016 (Computer Science Research Notes (CSRN) 2601)
ISBN: 978-80-86943-57-2
pp.1-8
International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG) <24, 2016, Plzen, Czech Republic>
English
Conference Paper, Electronic Publication
Fraunhofer IGD, Institutsteil Rostock ()
Fraunhofer IGD ()
Research Area: Computer vision (CV); video segmentation; image segmentation; optical flow; Guiding Theme: Visual Computing as a Service

Abstract
Foreground-Background Segregation has been intensively researched in the last decades as it is an important first step in many Computer Vision tasks. Nonetheless, there are still many open questions in this area and in this paper we focus on a special surveillance scenario where a static camera monitors a predefined region. This restrain makes some aspects easier and good results could be achieved with Background Subtraction methods. However, these only work pixelwise and lack the spatial component completely. We suggest an approach to add the crucial spatial information to the segmentations with Dense Optical Flows. For this, a number of successive images are taken from the video to compute the Trajectories of the pixels through these frames. This enables us to fuse the information from the several images and use this for segmentation. The algorithm was evaluated on a video from a surveillance camera and showed promising results.

: http://publica.fraunhofer.de/documents/N-445015.html