Paper Info
Title
Accelerating bioinspired lateral interaction in accumulative computation for real-time moving object detection with graphics processing units
Abstract
Biologically-inspired computer vision is a research area that offers prominent directions in a large variety of fields. Several processing algorithms inspired in natural vision enable detecting moving objects from video sequences so far. One example is lateral interaction in accumulative computation (LIAC), a classical bioinspired method that has been applied to numerous environments and applications. LIAC is the implementation for computer vision of two biologically-inspired methods denominated algorithmic lateral interaction and accumulative computation. The method has traditionally reached high precision but unfortunately requires high computing times. This paper introduces a proposal based on graphics processing units in order to speed up the original sequential code. This way not only excellent performance in terms of accuracy is maintained, but also real-time is obtained. A speed-up of 67× from the parallel over its sequential counterpart is achieved for several tested video sequences.
Year
DOI
Venue
2019
10.1007/s11047-018-9690-1
Natural Computing
Keywords
Field
DocType
Motion detection,Acceleration,Graphics processing unit,Lateral interaction in accumulative computation
Graphics,Computer vision,Object detection,Motion detection,Artificial intelligence,Acceleration,Graphics processing unit,Machine learning,Mathematics,Computation,Speedup
Journal
Volume
Issue
ISSN
18
2
1572-9796
Citations 
PageRank 
References 
0
0.34
14
Authors
5
Name
Order
Citations
PageRank
José L. Sánchez125240.65
María T. López232128.80
Jose M. Pastor3444.62
Ana E. Delgado424316.85
Antonio Fernández-Caballero51317117.99