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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

10.1007/s10008-009-0893-3

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ISSN

1573-1405

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A TwoLayer Framework for Piecewise Linear Manifol

Authors: Jacob Foytik Vijayan K Asari
Publish Date: 2012/09/19
Volume: 101, Issue: 2, Pages: 270-287
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Abstract

Finegrain head pose estimation from imagery is an essential operation for many humancentered systems including pose independent face recognition and humancomputer interaction HCI systems It is only recently that estimation systems have evolved past coarse level classification of pose and concentrated on finegrain estimation In particular the state of the art of such systems consists of nonlinear manifold embedding techniques that capture the intrinsic relationship of a pose varying face dataset The success of these solutions can be attributed to the acknowledgment that image variation corresponding to pose change is nonlinear in nature Yet the algorithms are limited by the complexity of embedding functions that describe the relationship We present a pose estimation framework that seeks to describe the global nonlinear relationship in terms of localized linear functions A two layer system coarse/fine is formulated on the assumptions that coarse pose estimation can be performed adequately using supervised linear methods and fine pose estimation can be achieved using linear regressive functions if the scope of the pose manifold is limited A pose estimation system is implemented utilizing simple linear subspace methods and oriented Gabor and phase congruency features The framework is tested using widely accepted posevarying face databases FacePix30 and Pointing’04 and shown to perform fine head pose estimation with competitive accuracy when compared with state of the art nonlinear manifold methods

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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. Learning Discriminative Space–Time Action Parts from Weakly Labelled Videos
  8. Recognizing Fine-Grained and Composite Activities Using Hand-Centric Features and Script Data
  9. 3D Human Pose Tracking Priors using Geodesic Mixture Models
  10. Exemplar-Guided Similarity Learning on Polynomial Kernel Feature Map for Person Re-identification
  11. Ethnicity- and Gender-based Subject Retrieval Using 3-D Face-Recognition Techniques
  12. A Variational Approach to Video Registration with Subspace Constraints
  13. The Fisher-Rao Metric for Projective Transformations of the Line
  14. Planar Motion Estimation and Linear Ground Plane Rectification using an Uncalibrated Generic Camera
  15. Guest Editorial: Human Activity Understanding from 2D and 3D Data
  16. Fast and Stable Polynomial Equation Solving and Its Application to Computer Vision
  17. Robust Pose Recognition of the Obscured Human Body
  18. Teichmüller Shape Descriptor and Its Application to Alzheimer’s Disease Study
  19. Parsing Images into Regions, Curves, and Curve Groups
  20. Using Biologically Inspired Features for Face Processing
  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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