Change-driven data flow image processing architecture for optical flow computation

被引：0
|
作者：
Julio C. Sosa
Jose A. Boluda
Fernando Pardo
Rocío Gómez-Fabela
机构：
[1] Escuela Superior de Cómputo—I.P.N.,Departamento de Sistemas Electrónicos
[2] Universitat de València,Departament d’Informàtica
来源：
Journal of Real-Time Image Processing | 2007年 / 2卷
关键词：
Motion estimation; Optical flow computation; Data flow architectures;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Optical flow computation has been extensively used for motion estimation of objects in image sequences. The results obtained by most optical flow techniques are computationally intensive due to the large amount of data involved. A new change-based data flow pipelined architecture has been developed implementing the Horn and Schunk smoothness constraint; pixels of the image sequence that significantly change, fire the execution of the operations related to the image processing algorithm. This strategy reduces the data and, combined with the custom hardware implemented, it achieves a significant optical flow computation speed-up with no loss of accuracy. This paper presents the bases of the change-driven data flow image processing strategy, as well as the implementation of custom hardware developed using an Altera Stratix PCI development board.
引用
收藏
页码：259 / 270
页数：11
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