Chaotic phase synchronization for visual selection

Chaotic phase synchronization among coupled oscillators is a phenomenon of interest in many physical and engineering systems. It has also been observed in biological systems, where groups of different functional units interact with each other in order to produce coherent behaviors in higher levels. While biological systems have facility to capture salient object(s) in a given scene, visual selection is still a challenging task to artificial visual systems. In this paper, a visual selection mechanism based on chaotic phase synchronization is proposed. Oscillators representing the salient object in a given scene are phase synchronized, while no synchronization is observed for background objects. In this way, the salient object is highlighted. Due to the modeling by phase synchronization instead of complete synchronization, the proposed model is robust, biologically inspired and good simulation results were achieved.

[1]  Kurths,et al.  Phase synchronization of chaotic oscillators. , 1996, Physical review letters.

[2]  Roman Borisyuk,et al.  Object selection by an oscillatory neural network. , 2002, Bio Systems.

[3]  R. Eckhorn,et al.  Coherent oscillations: A mechanism of feature linking in the visual cortex? , 1988, Biological Cybernetics.

[4]  Roseli A. Francelin Romero,et al.  A Visual Selection Mechanism Based on a Pulse-Coupled Neural Network , 2007, 2007 International Joint Conference on Neural Networks.

[5]  Ch. von der Malsburg,et al.  A neural cocktail-party processor , 1986, Biological Cybernetics.

[6]  D. Wang,et al.  The time dimension for scene analysis , 2005, IEEE Transactions on Neural Networks.

[7]  Nizam Omar,et al.  Locally coupled chaotic oscillator network for scene segmentation , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

[8]  J. Wolfe,et al.  What attributes guide the deployment of visual attention and how do they do it? , 2004, Nature Reviews Neuroscience.

[9]  Jürgen Kurths,et al.  Synchronization: Phase locking and frequency entrainment , 2001 .

[10]  W. Singer,et al.  Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties , 1989, Nature.

[11]  Paul H. E. Tiesinga,et al.  Attentional modulation of firing rate and synchrony in a model cortical network , 2005, Journal of Computational Neuroscience.

[12]  R. Desimone,et al.  Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention , 2001, Science.

[13]  Walter J. Jermakowicz,et al.  Neural networks a century after Cajal , 2007, Brain Research Reviews.

[14]  Liang Zhao,et al.  A network of dynamically coupled chaotic maps for scene segmentation , 2001, IEEE Trans. Neural Networks.

[15]  Brian Scassellati,et al.  A Behavioral Analysis of Computational Models of Visual Attention , 2007, International Journal of Computer Vision.

[16]  Grigory V. Osipov,et al.  PHASE SYNCHRONIZATION EFFECTS IN A LATTICE OF NONIDENTICAL ROSSLER OSCILLATORS , 1997 .

[17]  Vittorio Dante,et al.  A software-hardware selective attention system , 2004, Neurocomputing.

[18]  E. Fetz,et al.  Coherent 25- to 35-Hz oscillations in the sensorimotor cortex of awake behaving monkeys. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[19]  DeLiang Wang,et al.  Object selection based on oscillatory correlation , 1999, Neural Networks.

[20]  Roseli A. Francelin Romero,et al.  Visual Selection and Shifting Mechanisms Based on a Network of Chaotic Wilson-Cowan Oscillators , 2007, Third International Conference on Natural Computation (ICNC 2007).

[21]  DeLiang Wang,et al.  Image Segmentation Based on Oscillatory Correlation , 1997, Neural Computation.

[22]  Deliang Wang,et al.  Global competition and local cooperation in a network of neural oscillators , 1995 .

[23]  J. Martinerie,et al.  The brainweb: Phase synchronization and large-scale integration , 2001, Nature Reviews Neuroscience.

[24]  Nizam Omar,et al.  Scene Segmentation of the Chaotic oscillator Network , 2000, Int. J. Bifurc. Chaos.

[25]  John K. Tsotsos On the relative complexity of active vs. passive visual search , 2004, International Journal of Computer Vision.

[26]  C. Leeuwen,et al.  Scale-invariant fluctuations of the dynamical synchronization in human brain electrical activity , 2003, Neuroscience Letters.

[27]  Marcia Grabowecky,et al.  Attention induces synchronization-based response gain in steady-state visual evoked potentials , 2007, Nature Neuroscience.

[28]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

[29]  Steven Yantis,et al.  How visual salience wins the battle for awareness , 2005, Nature Neuroscience.

[30]  Hansel,et al.  Synchronization and computation in a chaotic neural network. , 1992, Physical review letters.

[31]  Christoph von der Malsburg,et al.  The Correlation Theory of Brain Function , 1994 .

[32]  W. Singer,et al.  Interhemispheric synchronization of oscillatory neuronal responses in cat visual cortex , 1991, Science.

[33]  Jürgen Kurths,et al.  Synchronization - A Universal Concept in Nonlinear Sciences , 2001, Cambridge Nonlinear Science Series.

[34]  Christof Koch,et al.  A model for the neuronal implementation of selective visual attention based on temporal correlation among neurons , 1994, Journal of Computational Neuroscience.