AN EFFICIENT RECONFIGURABLE ARCHITECTURE TO IMPLEMENT DENSE STEREO VISION ALGORITHM USING HIGH-LEVEL SYNTHESIS.

被引：4

作者：

Ibarra-Manzano, Mario Alberto ^{[1
]}

Devy, Michel ^{[2
]}

Boizard, Jean-Louis ^{[2
]}

Lacroix, Pierre ^{[2
]}

Fourniols, Jean-Yves ^{[2
]}

机构：

[1] CNRS, LAAS, 7 Ave Colonel Roche, F-31077 Toulouse, France

[2] CNRS, Univ Toulouse 1, INSA, IINP ISAE LAAS UPS, F-31077 Toulouse, France

来源：

FPL: 2009 INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE LOGIC AND APPLICATIONS | 2009年

关键词：

D O I：

10.1109/FPL.2009.5272490

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This article presents a reconfigurable architecture to calculate a dense disparity map of two stereo images based on census transform. This architecture is simplified and efficient as a result of binary operations and integer arithmetic used by census transform. Our architecture was prototyped using GAUT which is a practical tool to develop high-level synthesis. We take advantage of GAUT rapid prototyping to implement different architectures and to make a general comparison among them, that lets us to optimize the architecture, and at the same time, to improve the system's performance. The optimization and the resource saving rend our architecture an interesting option to solve the problem of stereo vision in real time, quite used in autonomous navigation.

引用

页码：444 / +

页数：2

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