AUTONOMOUS CAMERA CONTROL BY NEURAL MODELS IN ROBOTIC VISION SYSTEMS

Tyler W. Garaas, Frank Marino, Marc Pomplun

Abstract

Recently there has been growing interest in creating large-scale simulations of certain areas in the brain. The areas that are receiving the overwhelming focus are visual in nature, which may provide a means to compute some of the complex visual functions that have plagued AI researchers for many decades; robust object recognition, for example. Additionally, with the recent introduction of cheap computational hardware capable of computing at several teraflops, real-time robotic vision systems will likely be implemented using simplified neural models based on their slower, more realistic counterparts. This paper presents a series of small neural networks that can be integrated into a neural model of the human retina to automatically control the white-balance and exposure parameters of a standard video camera to optimize the computational processing performed by the neural model. Results of a sample implementation including a comparison with proprietary methods are presented. One strong advantage that these integrated sub-networks possess over proprietary mechanisms is that ‘attention’ signals could be used to selectively optimize areas of the image that are most relevant to the task at hand.

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Paper Citation


in Harvard Style

W. Garaas T., Marino F. and Pomplun M. (2009). AUTONOMOUS CAMERA CONTROL BY NEURAL MODELS IN ROBOTIC VISION SYSTEMS . In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-674-000-9, pages 305-311. DOI: 10.5220/0002217303050311


in Bibtex Style

@conference{icinco09,
author={Tyler W. Garaas and Frank Marino and Marc Pomplun},
title={AUTONOMOUS CAMERA CONTROL BY NEURAL MODELS IN ROBOTIC VISION SYSTEMS},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2009},
pages={305-311},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002217303050311},
isbn={978-989-674-000-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - AUTONOMOUS CAMERA CONTROL BY NEURAL MODELS IN ROBOTIC VISION SYSTEMS
SN - 978-989-674-000-9
AU - W. Garaas T.
AU - Marino F.
AU - Pomplun M.
PY - 2009
SP - 305
EP - 311
DO - 10.5220/0002217303050311