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Neural model of biological motion recognition based on shading cues

Point-light or stick-figure biological motion stimuli, due to the absence of depth cues, can induce bistable perception, where the walker is perceived as heading in two alternating directions [1, 2]. Psychophysical studies suggested an importance of depth cues for biological motion perception [3]. However, neural models of biological motion perception so far have focused on the processing of features that characterize the 2D structure and motion of the human body [4, 5]. We extend such models for the processing of shading cues in order to analyze the three-dimensional structure of walkers from monocular stimuli.

Model

As extension of a learning-based neural model [4], we add a 'shading pathway' that computes the internal contrast gradients that vary with the 3D view of the walker, even if the silhouette information remains identical (Figure 1A-C). The model exploits physiologically plausible operations. After suppression of strong external luminance gradients caused by the boundaries of the silhouette, internal luminance gradient features are extracted by a hierarchy of neural detectors. These gradient features, combined with the shape features extracted by the form pathway of the model in [4], are used as input for 'snapshot neurons', RBF units that detect 3D body shapes (Figure 1D). These model neurons are embedded within a two-dimensional recurrent neural field [6] that jointly represents the sequential temporal structure of the stimulus and the view of the walker.

Results

The neural field dynamics reproduces perceptual multi-stability and spontaneous perceptual switching between stimulus views, observed for silhouette stimuli in psychophysical experiments [1, 2]. It also reproduces 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.

Figure 1
figure1

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.

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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.

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Correspondence to Leonid A Fedorov or Martin A Giese.

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This article is published under license to BioMed Central Ltd. 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.

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Fedorov, L.A., Giese, M.A. Neural model of biological motion recognition based on shading cues. BMC Neurosci 16, P81 (2015). https://doi.org/10.1186/1471-2202-16-S1-P81

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Keywords

  • Neural Model
  • Biological Motion
  • Neural Field
  • Motion Recognition
  • Gradient Feature