Title
An optimized stereo vision implementation for embedded systems: application to RGB and Infra-Red images
Abstract
The aim of this paper is to demonstrate the applicability and the effectiveness of a computationally demanding stereo-matching algorithm in different low-cost and low-complexity embedded devices, by focusing on the analysis of timing and image quality performances. Various optimizations have been implemented to allow its deployment on specific hardware architectures while decreasing memory and processing time requirements: (1) reduction of color channel information and resolution for input images; (2) low-level software optimizations such as parallel computation, replacement of function calls or loop unrolling; (3) reduction of redundant data structures and internal data representation. The feasibility of a stereo vision system on a low-cost platform is evaluated by using standard datasets and images taken from infra-red cameras. Analysis of the resulting disparity map accuracy with respect to a full-size dataset is performed as well as the testing of suboptimal solutions.
Year
DOI
Venue
2016
10.1007/s11554-014-0461-7
J. Real-Time Image Processing
Keywords
Field
DocType
Stereo vision, Embedded optimization, Embedded systems, Smart camera, Near infra-red
Stereo cameras,Computer science,Stereopsis,Smart camera,Image quality,Real-time computing,Artificial intelligence,RGB color model,Loop unrolling,Computer vision,Channel (digital image),Embedded system,Computer stereo vision
Journal
Volume
Issue
ISSN
12
4
1861-8219
Citations 
PageRank 
References 
4
0.37
41
Authors
5
Name
Order
Citations
PageRank
Simone Madeo1151.23
Riccardo Pelliccia2101.63
claudio salvadori3262.28
Jesús Martínez del Rincón413612.23
Jean-christophe Nebel523819.58