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Itti, Models of Bottom-Up and Top-Down Visual Attention, California Institute of Technology, Jan 2000. Niebur, A Model of Saliency-Based Visual Attention for Rapid Scene Analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.

Originally, this toolkit was developed to implement our model of bottom-up, saliency-based visual attention, as described in the following scientific articles (all available in PDF format from ): Neuromorphic algorithms are motivated by and closely follow the architecture of biological brains. This toolkit provides a number of C++ classes to assist you in developing neuromorphic vision algorithms. You should have received a copy of the GNU General Public License along with the iLab Neuromorphic Vision C++ Toolkit if not, write to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA. See the GNU General Public License for more details. The iLab Neuromorphic Vision C++ Toolkit is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. The iLab Neuromorphic Vision C++ Toolkit is free software you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation either version 2 of the License, or (at your option) any later version. This file is part of the iLab Neuromorphic Vision C++ Toolkit. patent ``Computation of Intrinsic Perceptual Saliency in Visual Environments, and Applications'' by Christof Koch and Laurent Itti, California Institute of Technology, 2001 (patent pending application number 09/912,225 filed Jsee for current status) Major portions of the iLab Neuromorphic Vision C++ Toolkit are protected under the U.S.

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