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Title of Journal: Int J Comput Vis

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Abbravation: International Journal of Computer Vision

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Springer US

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DOI

10.1002/19960403nt4

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1573-1405

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Using Biologically Inspired Features for Face Proc

Authors: Ethan Meyers Lior Wolf
Publish Date: 2007/07/12
Volume: 76, Issue: 1, Pages: 93-104
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Abstract

In this paper we show that a new set of visual features derived from a feedforward model of the primate visual object recognition pathway proposed by Riesenhuber and Poggio RP Model Nature Neurosci 2111019–1025 1999 is capable of matching the performance of some of the best current representations for face identification and facial expression recognition Previous work has shown that the Riesenhuber and Poggio Model features can achieve a high level of performance on object recognition tasks Serre T et al in IEEE Comput Vis Pattern Recognit 2994–1000 2005 Here we modify the RP model in order to create a new set of features useful for face identification and expression recognition Results from tests on the FERET ORL and AR datasets show that these features are capable of matching and sometimes outperforming other top visual features such as local binary patterns Ahonen T et al in 8th European Conference on Computer Vision pp 469–481 2004 and histogram of gradient features Dalal N Triggs B in International Conference on Computer Vision Pattern Recognition pp 886–893 2005 Having a model based on shared lower level features and face and object recognition specific higher level features is consistent with findings from electrophysiology and functional magnetic resonance imaging experiments Thus our model begins to address the complete recognition problem in a biologically plausible way

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Other Papers In This Journal:
  1. Growing Regression Tree Forests by Classification for Continuous Object Pose Estimation
  2. Objects, Actions, Places
  3. Hierarchical Shape Segmentation and Registration via Topological Features of Laplace-Beltrami Eigenfunctions
  4. Geometric Image Parsing in Man-Made Environments
  5. On Taxonomies for Multi-class Image Categorization
  6. Full and Partial Symmetries of Non-rigid Shapes
  7. A Two-Layer Framework for Piecewise Linear Manifold-Based Head Pose Estimation
  8. Learning Discriminative Space–Time Action Parts from Weakly Labelled Videos
  9. Recognizing Fine-Grained and Composite Activities Using Hand-Centric Features and Script Data
  10. 3D Human Pose Tracking Priors using Geodesic Mixture Models
  11. Exemplar-Guided Similarity Learning on Polynomial Kernel Feature Map for Person Re-identification
  12. Ethnicity- and Gender-based Subject Retrieval Using 3-D Face-Recognition Techniques
  13. A Variational Approach to Video Registration with Subspace Constraints
  14. The Fisher-Rao Metric for Projective Transformations of the Line
  15. Planar Motion Estimation and Linear Ground Plane Rectification using an Uncalibrated Generic Camera
  16. Guest Editorial: Human Activity Understanding from 2D and 3D Data
  17. Fast and Stable Polynomial Equation Solving and Its Application to Computer Vision
  18. Robust Pose Recognition of the Obscured Human Body
  19. Teichmüller Shape Descriptor and Its Application to Alzheimer’s Disease Study
  20. Parsing Images into Regions, Curves, and Curve Groups
  21. Two-View Motion Segmentation with Model Selection and Outlier Removal by RANSAC-Enhanced Dirichlet Process Mixture Models
  22. Information-Theoretic Active Polygons for Unsupervised Texture Segmentation
  23. Virtual Volumetric Graphics on Commodity Displays Using 3D Viewer Tracking
  24. 3-D Symmetry Detection and Analysis Using the Pseudo-polar Fourier Transform
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