NDLI: A dynamic attention system that reorients to unexpected motion in real-world traffic environments

Content Provider	IEEE Xplore Digital Library
Author	Heracles, M. Korner, U. Michalke, T. Sagerer, G. Fritsch, J. Goerick, C.
Copyright Year	2009
Description	Author affiliation: Honda Research Institute Europe, D-63073 Offenbach/ Main, Germany (Michalke, T.; Sagerer, G.; Fritsch, J.; Goerick, C.) \|\| Research Institute for Cognition and Robotics, Bielefeld University, D-33615 Bielefeld, Germany (Heracles, M.; Korner, U.)
Abstract	In this paper we propose a system architecture that extends the current state-of-the-art in computational visual attention by incorporating the biological concept of ventral attention. According to recent findings regarding the neurobiological foundations of attention, there exist two separate but interacting attention systems in the human brain: the dorsal attention system and the ventral attention system. As opposed to the well-known computational concepts of bottom-up and top-down saliency, which both correspond to the dorsal attention system, the ventral attention system is sensitive to behavior-relevant stimuli that are unexpected (i.e. not top-down salient), independent of their perceptual saliency (bottom-up saliency). This results in a dynamic interplay between top-down saliency, bottom-up saliency and ventral attention in the proposed system architecture, enabling the system to redirect its focus of attention to important stimuli while being absorbed in a task, even if their perceptual saliency is low. Our technical system instance implementing the proposed architecture integrates several state-of-the-art methods in a coherent system and concentrates on unexpected motion as a first technical account of ventral attention. In our experiments, we demonstrate that the ventral attention enables our system to detect and reorient to important situations in real-world traffic environments that are relevant for the behavior of driving.
Starting Page	1735
Ending Page	1742
File Size	1756194
Page Count	8
File Format	PDF
ISBN	9781424438037
DOI	10.1109/IROS.2009.5354387
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Biology computing Computer vision Intelligent robots USA Councils Computer architecture Focusing Information filtering Information filters Humanoid robots
Content Type	Text
Resource Type	Article

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