Hierarchical , Localized Saliency Computations Solve the Visual Feature Binding Problem

Computational vision has a long history of proposing methods for decomposing a visual signal into components. What has been far more elusive is how to recombine those components into a whole, a problem known as the binding problem. Although several proposals have appeared, the approaches and their demonstrations seem weak at best. This paper proposes a novel solution for a significant portion of the binding problem, namely, the re-combination of visual features into larger patterns and their localization in the image. The solution requires the abandonment of the nearly ubiquitous single saliency map and the adoption of a hierarchical, localized computation of saliency that is dependent on local neural selectivity constraints. This strategy has been demonstrated within a fully implemented model that attends to simple motion patterns in image sequences.

[1]  John K. Tsotsos,et al.  Modeling Visual Attention via Selective Tuning , 1995, Artif. Intell..

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

[3]  J. Orbach.  Principles of Neurodynamics. Perceptrons and the Theory of Brain Mechanisms. , 1962 .

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

[5]  R. Desimone,et al.  The Role of Neural Mechanisms of Attention in Solving the Binding Problem , 1999, Neuron.

[6]  John K. Tsotsos,et al.  Attending to visual motion , 2005, Comput. Vis. Image Underst..

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

[8]  A. Treisman,et al.  A feature-integration theory of attention , 1980, Cognitive Psychology.

[9]  S Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

[10]  A. Treisman,et al.  Illusory conjunctions in the perception of objects , 1982, Cognitive Psychology.

[11]  Christoph von der Malsburg,et al.  The What and Why of Binding: Review The Modeler's Perspective , 1999 .

[12]  H B Barlow,et al.  Single units and sensation: a neuron doctrine for perceptual psychology? , 1972, Perception.

[13]  D. J. Felleman,et al.  Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.

[14]  A. Roskies.  The Binding Problem , 1999, Neuron.

[15]  J. Anthony Movshon,et al.  Review A Critical Evaluation of the Temporal Binding Hypothesis , 1999 .

[16]  John K. Tsotsos.  The Complexity of Perceptual Search Tasks , 1989, IJCAI.

[17]  Christos H. Papadimitriou,et al.  The complexity of recognizing polyhedral scenes , 1985, 26th Annual Symposium on Foundations of Computer Science (sfcs 1985).

[18]  I. Biederman,et al.  Dynamic binding in a neural network for shape recognition. , 1992, Psychological review.

[19]  John K. Tsotsos.  Analyzing vision at the complexity level , 1990, Behavioral and Brain Sciences.

[20]  T. Poggio,et al.  Are Cortical Models Really Bound by the “Binding Problem”? , 1999, Neuron.