Parallelization of the optical flow computation in sequences from moving cameras

This paper presents a flexible and scalable approach to the parallelization of the computation of optical flow. This approach is based on data parallel distribution. Images are divided into several subimages processed by a software pipeline while respecting dependencies between computation stages. T...

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Bibliographic Details
Published in:EURASIP journal on image and video processing 2014-03, Vol.2014 (1), p.1-19, Article 18
Main Authors: Garcia-Dopico, Antonio, Pedraza, José Luis, Nieto, Manuel, Pérez, Antonio, Rodríguez, Santiago, Navas, Juan
Format: Article
Language:English
Subjects:
Biometrics
Cameras
Computation
Computer programs
Engineering
Flexibility
Image Processing and Computer Vision
Parallel processing
Pattern Recognition
Pipelines
Roads
Signal,Image and Speech Processing
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Summary:This paper presents a flexible and scalable approach to the parallelization of the computation of optical flow. This approach is based on data parallel distribution. Images are divided into several subimages processed by a software pipeline while respecting dependencies between computation stages. The parallelization has been implemented in three different infrastructures: shared, distributed memory, and hybrid to show its conceptual flexibility and scalability. A significant improvement in performance was obtained in all three cases. These versions have been used to compute the optical flow of video sequences taken in adverse conditions, with a moving camera and natural-light conditions, on board a conventional vehicle traveling on public roads. The parallelization adopted has been developed from the analysis of dependencies presented by the well-known Lucas-Kanade algorithm, using a sequential version developed at the University of Porto as the starting point.
ISSN:1687-5281
1687-5176
1687-5281
DOI:10.1186/1687-5281-2014-18