Paper Info
Title
A fast and scalable system for visual attention, object based attention and object recognition for humanoid robots
Abstract
In this paper, we present a novel approach towards the integration of visual attention, object based attention and object recognition. Our system is scalable in regard to the required framerate or usage of computational power. Therefore, it is perfectly suited for robotic applications, where time is a crucial factor. We enhance and evaluate our previously presented visual attention system based on sampled template collation (STC) to fit into a humanoid robotic context by dynamically adjusting the required computational speed. We modify STC for object-based attention to segment the attended object from the surrounding background. Subsequently we combine it with a biologically-inspired object recognition system. We show that our approach significantly improves the recognition accuracy.
Year
DOI
Venue
2014
10.1109/HUMANOIDS.2014.7041378
Humanoid Robots
Keywords
Field
DocType
humanoid robots,object recognition,robot vision,STC,biologically-inspired object recognition system,humanoid robots,object based attention,object-based attention,sampled template collation,visual attention
Computer vision,Object-based attention,3D single-object recognition,Visualization,Computer science,Object model,Visual attention,Artificial intelligence,Humanoid robot,Scalability,Cognitive neuroscience of visual object recognition
Conference
ISSN
Citations 
PageRank 
2164-0572
0
0.34
References 
Authors
11
2
Name
Order
Citations
PageRank
Andreas Holzbach100.34
Gordon Cheng21250115.33