DocumentCode :
250518
Title :
A concurrent real-time biologically-inspired visual object recognition system
Author :
Holzbach, Andreas ; Cheng, Gordon
Author_Institution :
Inst. for Cognitive Syst., Tech. Univ. Muunchen, München, Germany
fYear :
2014
fDate :
May 31 2014-June 7 2014
Firstpage :
3201
Lastpage :
3206
Abstract :
In this paper, we present an biologically-motivated object recognition system for robots and vision tasks in general. Our approach is based on a hierarchical model of the visual cortex for feature extraction and rapid scene categorization. We modify this static model to be usable in time-crucial real-world scenarios by applying methods for optimization from signal detection theory, information theory, signal processing and linear algebra. Our system is more robust to clutter and supports object localization by approaching the binding problem in contrast to previous models. We show that our model outperforms the preceding model and that by our modifications we created a robust and fast system which integrates the capabilities of biological-inspired object recognition in a technical application.
Keywords :
feature extraction; object recognition; robot vision; biologically-motivated object recognition system; concurrent real-time biologically-inspired visual object recognition system; feature extraction; information theory; linear algebra; object localization; rapid scene categorization; robots; signal detection theory; signal processing; vision tasks; visual cortex; Biological system modeling; Brain modeling; Dictionaries; Graphics processing units; Object recognition; Training; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2014 IEEE International Conference on
Conference_Location :
Hong Kong
Type :
conf
DOI :
10.1109/ICRA.2014.6907319
Filename :
6907319
Link To Document :
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