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      Scene analysis in the natural environment

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          Abstract

          The problem of scene analysis has been studied in a number of different fields over the past decades. These studies have led to important insights into problems of scene analysis, but not all of these insights are widely appreciated, and there remain critical shortcomings in current approaches that hinder further progress. Here we take the view that scene analysis is a universal problem solved by all animals, and that we can gain new insight by studying the problems that animals face in complex natural environments. In particular, the jumping spider, songbird, echolocating bat, and electric fish, all exhibit behaviors that require robust solutions to scene analysis problems encountered in the natural environment. By examining the behaviors of these seemingly disparate animals, we emerge with a framework for studying scene analysis comprising four essential properties: (1) the ability to solve ill-posed problems, (2) the ability to integrate and store information across time and modality, (3) efficient recovery and representation of 3D scene structure, and (4) the use of optimal motor actions for acquiring information to progress toward behavioral goals.

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          Normalized cuts and image segmentation

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            Object perception as Bayesian inference.

            We perceive the shapes and material properties of objects quickly and reliably despite the complexity and objective ambiguities of natural images. Typical images are highly complex because they consist of many objects embedded in background clutter. Moreover, the image features of an object are extremely variable and ambiguous owing to the effects of projection, occlusion, background clutter, and illumination. The very success of everyday vision implies neural mechanisms, yet to be understood, that discount irrelevant information and organize ambiguous or noisy local image features into objects and surfaces. Recent work in Bayesian theories of visual perception has shown how complexity may be managed and ambiguity resolved through the task-dependent, probabilistic integration of prior object knowledge with image features.
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              Remembering the past and imagining the future: a neural model of spatial memory and imagery.

              The authors model the neural mechanisms underlying spatial cognition, integrating neuronal systems and behavioral data, and address the relationships between long-term memory, short-term memory, and imagery, and between egocentric and allocentric and visual and ideothetic representations. Long-term spatial memory is modeled as attractor dynamics within medial-temporal allocentric representations, and short-term memory is modeled as egocentric parietal representations driven by perception, retrieval, and imagery and modulated by directed attention. Both encoding and retrieval/imagery require translation between egocentric and allocentric representations, which are mediated by posterior parietal and retrosplenial areas and the use of head direction representations in Papez's circuit. Thus, the hippocampus effectively indexes information by real or imagined location, whereas Papez's circuit translates to imagery or from perception according to the direction of view. Modulation of this translation by motor efference allows spatial updating of representations, whereas prefrontal simulated motor efference allows mental exploration. The alternating temporal-parietal flows of information are organized by the theta rhythm. Simulations demonstrate the retrieval and updating of familiar spatial scenes, hemispatial neglect in memory, and the effects on hippocampal place cell firing of lesioned head direction representations and of conflicting visual and ideothetic inputs. (c) 2007 APA, all rights reserved.
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                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                03 January 2014
                01 April 2014
                2014
                : 5
                : 199
                Affiliations
                [1] 1Department of Electrical Engineering and Computer Science, Case Western Reserve University Cleveland, OH, USA
                [2] 2Helen Wills Neuroscience Institute, School of Optometry, Redwood Center for Theoretical Neuroscience, University of California at Berkeley Berkeley, CA, USA
                [3] 3Department of Biology, University of Southern Denmark Odense, Denmark
                [4] 4Department of Psychology and Institute for Systems Research, University of Maryland College Park, MD, USA
                Author notes

                Edited by: Laurence T. Maloney, Stanford University, USA

                Reviewed by: Wolfgang Einhauser, Philipps-Universität Marburg, Germany; Sébastien M. Crouzet, Charité University Medicine, Germany

                *Correspondence: Michael S. Lewicki, Department of Electrical Engineering and Computer Science, Case Western Reserve University, Glennan Building, Room 321, 10900 Euclid Avenue, Cleveland, OH 44106-7071, USA e-mail: michael.lewicki@ 123456case.edu

                This article was submitted to Perception Science, a section of the journal Frontiers in Psychology.

                Article
                10.3389/fpsyg.2014.00199
                3978336
                24744740
                53c2e323-b9d1-43c6-91ea-ea3b00015377
                Copyright © 2014 Lewicki, Olshausen, Surlykke and Moss.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 01 November 2013
                : 20 February 2014
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 173, Pages: 21, Words: 0
                Categories
                Psychology
                Review Article

                Clinical Psychology & Psychiatry
                active perception,auditory streaming,echolocation,vision,electroreception,scene analysis,top-down processes,neuroethology

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