Get 20M+ Full-Text Papers For Less Than $1.50/day. Subscribe now for You or Your Team.

Learn More →

Neural model of biological motion recognition based on shading cues

Neural model of biological motion recognition based on shading cues Fedorov and Giese BMC Neuroscience 2015, 16(Suppl 1):P81 http://www.biomedcentral.com/1471-2202/16/S1/P81 POSTER PRESENTATION Open Access Neural model of biological motion recognition based on shading cues * * Leonid A Fedorov , Martin A Giese From 24th Annual Computational Neuroscience Meeting: CNS*2015 Prague, Czech Republic. 18-23 July 2015 Point-light or stick-figure biological motion stimuli, due to silhouette information remains identical (Figure 1A-C). the absence of depth cues, can induce bistable perception, The model exploits physiologically plausible operations. where the walker is perceived as heading in two alternat- After suppression of strong external luminance gradients ing directions [1,2]. Psychophysical studies suggested an caused by the boundaries of the silhouette, internal lumi- importance of depth cues for biological motion perception nance gradient features are extracted by a hierarchy of [3]. However, neural models of biological motion percep- neural detectors. These gradient features, combined with tion so far have focused on the processing of features that the shape features extracted by the form pathway of the characterize the 2D structure and motion of the human model in [4], are used as input for ‘snapshot neurons’,RBF body [4,5]. We extend such models for the processing of units that detect 3D body shapes (Figure 1D). These model shading cues in order to analyze the three-dimensional neurons are embedded within a two-dimensional recurrent structure of walkers from monocular stimuli. neural field [6] that jointly represents the sequential tem- poral structure of the stimulus and the view of the walker. Model As extension of a learning-based neural model [4], we add a Results ‘shading pathway’ that computes the internal contrast gra- The neural field dynamics reproduces perceptual multi- dients that vary with the 3D view of the walker, even if the stability and spontaneous perceptual switching between Figure 1 A. Snapshot from a walker stimulus, rendered from a -45° side view. Vectors indicate internal luminance gradients, extracted by the internal gradient detectors of the model. B. Silhouette stimulus without shading cues is ambiguous and compatible with view angles ±45°. C. Snapshot and internal shading gradients for +45° side view. D. ‘Shading pathway’. After suppression of strong boundary gradients, internal luminance gradients are extracted, using a hierarchy of neural detectors similar to a convolutional network. At the highest level is formed by ‘snapshot neurons’, RBF units that have been trained with keyframes from 3D walker movies, which are embedded in a dynamic neural field. * Correspondence: leonid.fedorov@cin.uni-tuebingen.de; martin.giese@uni- tuebingen.de Section f. Computational Sensomotorics, Dept. of Cogn. Neurology, CIN/ HIH, University Clinic Tuebingen, Tuebingen, Germany © 2015 Fedorov and Giese This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Fedorov and Giese BMC Neuroscience 2015, 16(Suppl 1):P81 Page 2 of 2 http://www.biomedcentral.com/1471-2202/16/S1/P81 stimulus views, observed for silhouette stimuli in psy- chophysical experiments [1,2].Italsoreproduces the disambiguation by addition of shading information and a new perceptual illusion, which illustrates a lighting- from-above prior in the processing of biological motion stimuli. Acknowledgements Supported by EC FP7 ABC PITN-GA-011-290011, HBP FP7-604102, Koroibot FP7-611909, COGIMON H2020-644727, DFG GI 305/4-1, DFG GZ: KA 1258/15- 1, and BMBF, FKZ: 01GQ1002A. Published: 18 December 2015 References 1. Vanrie J, Dekeyser M, Verfaillie K: Bistability and biasing effects in the perception of ambiguous point-light walkers. Perception 2004, 33:547-560. 2. Vangeneugden J, De Mazière P, Van Hulle M, Jaeggli T, Van Gool L, Vogels R: Distinct mechanisms for coding of visual actions in macaque temporal cortex. J Neurosci 2011, 31(2):385-401. 3. Vanrie J, Verfaillie K: Perceiving depth in point-light actions. Perc Psychophys 2006, 68(4):601-612. 4. Giese MA, Poggio T: Neural mechanisms for the recognition of biological movements and action. Nat Rev Neurosci 2003, 4:179-192. 5. Lange J, Lappe M: A model of biological motion perception from configural form cues. J Neurosci 2006, 26:2894-2906. 6. Amari S: Dynamics of pattern formation in lateral inhibition type neural fields. Biol Cyb 1977, 27:77-87. doi:10.1186/1471-2202-16-S1-P81 Cite this article as: Fedorov and Giese: Neural model of biological motion recognition based on shading cues. BMC Neuroscience 2015 16(Suppl 1):P81. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Neuroscience Springer Journals

Neural model of biological motion recognition based on shading cues

BMC Neuroscience , Volume 16 (1) – Dec 18, 2015

Loading next page...
 
/lp/springer-journals/neural-model-of-biological-motion-recognition-based-on-shading-cues-EmZR0R70T1

References (6)

Publisher
Springer Journals
Copyright
Copyright © 2015 by Fedorov and Giese
Subject
Biomedicine; Neurosciences; Neurobiology; Animal Models
eISSN
1471-2202
DOI
10.1186/1471-2202-16-S1-P81
Publisher site
See Article on Publisher Site

Abstract

Fedorov and Giese BMC Neuroscience 2015, 16(Suppl 1):P81 http://www.biomedcentral.com/1471-2202/16/S1/P81 POSTER PRESENTATION Open Access Neural model of biological motion recognition based on shading cues * * Leonid A Fedorov , Martin A Giese From 24th Annual Computational Neuroscience Meeting: CNS*2015 Prague, Czech Republic. 18-23 July 2015 Point-light or stick-figure biological motion stimuli, due to silhouette information remains identical (Figure 1A-C). the absence of depth cues, can induce bistable perception, The model exploits physiologically plausible operations. where the walker is perceived as heading in two alternat- After suppression of strong external luminance gradients ing directions [1,2]. Psychophysical studies suggested an caused by the boundaries of the silhouette, internal lumi- importance of depth cues for biological motion perception nance gradient features are extracted by a hierarchy of [3]. However, neural models of biological motion percep- neural detectors. These gradient features, combined with tion so far have focused on the processing of features that the shape features extracted by the form pathway of the characterize the 2D structure and motion of the human model in [4], are used as input for ‘snapshot neurons’,RBF body [4,5]. We extend such models for the processing of units that detect 3D body shapes (Figure 1D). These model shading cues in order to analyze the three-dimensional neurons are embedded within a two-dimensional recurrent structure of walkers from monocular stimuli. neural field [6] that jointly represents the sequential tem- poral structure of the stimulus and the view of the walker. Model As extension of a learning-based neural model [4], we add a Results ‘shading pathway’ that computes the internal contrast gra- The neural field dynamics reproduces perceptual multi- dients that vary with the 3D view of the walker, even if the stability and spontaneous perceptual switching between Figure 1 A. Snapshot from a walker stimulus, rendered from a -45° side view. Vectors indicate internal luminance gradients, extracted by the internal gradient detectors of the model. B. Silhouette stimulus without shading cues is ambiguous and compatible with view angles ±45°. C. Snapshot and internal shading gradients for +45° side view. D. ‘Shading pathway’. After suppression of strong boundary gradients, internal luminance gradients are extracted, using a hierarchy of neural detectors similar to a convolutional network. At the highest level is formed by ‘snapshot neurons’, RBF units that have been trained with keyframes from 3D walker movies, which are embedded in a dynamic neural field. * Correspondence: leonid.fedorov@cin.uni-tuebingen.de; martin.giese@uni- tuebingen.de Section f. Computational Sensomotorics, Dept. of Cogn. Neurology, CIN/ HIH, University Clinic Tuebingen, Tuebingen, Germany © 2015 Fedorov and Giese This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Fedorov and Giese BMC Neuroscience 2015, 16(Suppl 1):P81 Page 2 of 2 http://www.biomedcentral.com/1471-2202/16/S1/P81 stimulus views, observed for silhouette stimuli in psy- chophysical experiments [1,2].Italsoreproduces the disambiguation by addition of shading information and a new perceptual illusion, which illustrates a lighting- from-above prior in the processing of biological motion stimuli. Acknowledgements Supported by EC FP7 ABC PITN-GA-011-290011, HBP FP7-604102, Koroibot FP7-611909, COGIMON H2020-644727, DFG GI 305/4-1, DFG GZ: KA 1258/15- 1, and BMBF, FKZ: 01GQ1002A. Published: 18 December 2015 References 1. Vanrie J, Dekeyser M, Verfaillie K: Bistability and biasing effects in the perception of ambiguous point-light walkers. Perception 2004, 33:547-560. 2. Vangeneugden J, De Mazière P, Van Hulle M, Jaeggli T, Van Gool L, Vogels R: Distinct mechanisms for coding of visual actions in macaque temporal cortex. J Neurosci 2011, 31(2):385-401. 3. Vanrie J, Verfaillie K: Perceiving depth in point-light actions. Perc Psychophys 2006, 68(4):601-612. 4. Giese MA, Poggio T: Neural mechanisms for the recognition of biological movements and action. Nat Rev Neurosci 2003, 4:179-192. 5. Lange J, Lappe M: A model of biological motion perception from configural form cues. J Neurosci 2006, 26:2894-2906. 6. Amari S: Dynamics of pattern formation in lateral inhibition type neural fields. Biol Cyb 1977, 27:77-87. doi:10.1186/1471-2202-16-S1-P81 Cite this article as: Fedorov and Giese: Neural model of biological motion recognition based on shading cues. BMC Neuroscience 2015 16(Suppl 1):P81. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit

Journal

BMC NeuroscienceSpringer Journals

Published: Dec 18, 2015

There are no references for this article.