DocumentCode :
248395
Title :
Optical Flow Motion Detection on Raspberry Pi
Author :
Baby, Rinu Merin ; Ahamed, Rooha Razmid
Author_Institution :
Electron. & Commun. Dept., RSET, Kochi, India
fYear :
2014
fDate :
27-29 Aug. 2014
Firstpage :
151
Lastpage :
152
Abstract :
This paper presents the implementation of Optical Flow Motion Detection algorithm on Raspberry Pi. The Lucas-Kanade method was chosen for the implementation. The algorithm works by comparing two successive image frames. To find out a displaced object, the algorithm tries to guess the direction of displaced object rather than scanning the second image for the matching pixel. This can be done by solving for the optical flow vector by assuming that the vector will be similar to a small neighbourhood surrounding the pixel. The algorithm was simulated using Python OpenCV. The implementation of Lucas-Kanade algorithm was successfully done on Raspberry Pi.
Keywords :
image matching; image motion analysis; image sequences; vectors; Lucas-Kanade method; Python OpenCV; Raspberry Pi; image frames; image matching; optical flow motion detection; optical flow vector; Adaptive optics; Integrated optics; Motion detection; Optical imaging; Optical sensors; Streaming media; Vectors; Lucas-Kanade; motion detection; optical flow;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computing and Communications (ICACC), 2014 Fourth International Conference on
Conference_Location :
Cochin
Print_ISBN :
978-1-4799-4364-7
Type :
conf
DOI :
10.1109/ICACC.2014.42
Filename :
6906011
Link To Document :
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