DocumentCode :
3694382
Title :
Detection of ascending and descending stairways by surface normal vectors
Author :
Daniel Wagner;Kathrin Kalischewski;Jörg Velten;Anton Kummert
Author_Institution :
Faculty of Electrical, Information and Media Engineering, University of Wuppertal, D-42119 Wuppertal, Germany
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
Persons with walking frames are often limited with respect to visual acuity and they are depending on assistance. To give them the possibility to move free and autonomous in their environment an intelligent assistance system is proposed which can be mounted on a walking frame is used to observe the scene in walking direction, and obstacles have to be detected. Especially, stairways represent a high risk of injury if a collapse occurs. For stairway recognition, an algorithm is proposed which estimates normal vectors by using a covariance matrix and this makes it possible to segment the point cloud data provided by the Kinect sensor. The calculation of surface normal vectors of these regions helps to detect ascending and descending stairways.
Keywords :
"Three-dimensional displays","Cameras","Legged locomotion","Covariance matrices","Robot sensing systems","Estimation","Feature extraction"
Publisher :
ieee
Conference_Titel :
Multidimensional (nD) Systems (nDS), 2015 IEEE 9th International Workshop on
Type :
conf
DOI :
10.1109/NDS.2015.7332646
Filename :
7332646
Link To Document :
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