DocumentCode
1997693
Title
Binocular Vision Based Drivable Region Fast Detection for Indoor Mobile Robot
Author
Qu Shengyue ; Meng Cai
Author_Institution
Image Process. Center, Beihang Univ., Beijing, China
fYear
2013
fDate
3-4 Dec. 2013
Firstpage
257
Lastpage
261
Abstract
A fast method based on binocular vision is proposed for mobile robot to detect drivable regions. First, the image is segmented into regions by searching contours. Second, part obstacle regions are determined by the vanishing line. Then, according to the different distribution of feature points extracted from the regions under the vanishing line, we use two different method to classify regions: various constraints-based region classification is used to classify regions including many feature points and homography-substraction-based region classification is used to classify regions including rare feature points. Finally, combining the two classification methods, we get the result of drivable region detection. The results of indoor and outdoor experiments show that the method can detect drivable regions quickly and robustly.
Keywords
feature extraction; image classification; image matching; image segmentation; mobile robots; object detection; path planning; probability; robot vision; binocular vision based drivable region fast detection; drivable region probabilities; feature classification; feature correspondence matching; feature point extraction; image segmentation; indoor experiments; indoor mobile robot; outdoor experiments; Accuracy; Cameras; Feature extraction; Gray-scale; Image segmentation; Mobile robots; Robustness; binocular vision; drivable region detection; feature classification; image segmentation; mobile robot;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems (GCIS), 2013 Fourth Global Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4799-2885-9
Type
conf
DOI
10.1109/GCIS.2013.47
Filename
6805944
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