DocumentCode :
1570355
Title :
Crosswalks recognition through CNNs for the bionic camera: Manual vs. automatic design
Author :
Radványi, Mihály ; Pazienza, Giovanni E. ; Karacs, Kristóf
Author_Institution :
Fac. of Inf. Technol., Pazmany Peter Catholic Univ., Budapest, Hungary
fYear :
2009
Firstpage :
315
Lastpage :
318
Abstract :
Although accessible pedestrian signals are more and more frequent at crosswalks in busy intersections, visually impaired people will not be able to get about independently until the infrastructure reaches full coverage on the routes they are using. In this paper, we present algorithms to detect and recognize pedestrian crosswalks developed in the framework of the research to create a Bionic Eyeglass, a mobile navigation and orientation device for blind and visually impaired people. We compare the results of manually designed algorithms with ones automatically generated via Genetic Programming.
Keywords :
cameras; genetic algorithms; handicapped aids; mobile computing; navigation; traffic engineering computing; CNN; accessible pedestrian signals; bionic camera; bionic eyeglass; crosswalks recognition; genetic programming; mobile navigation; pedestrian crosswalks; visually impaired people; Algorithm design and analysis; Cameras; Cellular networks; Cellular neural networks; Cellular phones; Computer networks; Information technology; Machine learning algorithms; Navigation; Prototypes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuit Theory and Design, 2009. ECCTD 2009. European Conference on
Conference_Location :
Antalya
Print_ISBN :
978-1-4244-3896-9
Electronic_ISBN :
978-1-4244-3896-9
Type :
conf
DOI :
10.1109/ECCTD.2009.5274981
Filename :
5274981
Link To Document :
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