Out of plane rotations
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2. 1. 3. Out-of-plane Rotations. Environment constraints Surveillance systems Car driver images ASM: Similarity does not remove 3D pose Multiple-view database Other approaches Non-linear models 3D models: multiple views. [email protected] Database.

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Out-of-plane Rotations

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Out of plane rotations

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Out-of-plane Rotations

  • Environment constraints

    • Surveillance systems

    • Car driver images

  • ASM:

    • Similarity does not remove 3D pose

    • Multiple-view database

  • Other approaches

    • Non-linear models

    • 3D models: multiple views

[email protected] Database


Projective geometry

Geometric operations by means of linear algebra

2D points are 3-component vectors

Multiple views of the same planar object can be related by homographies

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Projective Geometry

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Homographies

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Homographies

  • Homographies hold both for object or camera movements

  • The points must be coplanar

H


Coplanar face model

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Coplanar face model

  • Silhouette points are excluded (out of main plane)

  • Half the nose points are excluded (easy occlusion)

  • First iteration: At least 8 correspondences to compute H (4 2D-points)

Model Coordinates

Image Coordinates


Image matching

ASM Image Model (Similarity)

Gradient normal to the shape contour

Projective transformations

Do not preserve angles nor distance relationships

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Image Matching

H


Av@car database 40 people

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[email protected] Database (40 people)


Results

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Results

ASM

  • Training and test on multi-view data

  • Cross validation

PASM


Comparison to related work

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Comparison to related work

Ratios with respect to error on frontal images


Results training just a single view frontal

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Results training just a single view (frontal)

  • Training set: Frontal

  • Test set: Multilple views


Analysis of the single view case

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Analysis of the single-view case


Conclusions on pasm

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Conclusions on PASM

  • If multi-view dataset available

    • Almost invariant to rotations up to 60 degrees

  • Training only on frontal views

    • Considerably reduces (50%) variation of ASM due to viewpoint

  • Left-right rotations better handled than up-down nodding

  • Very difficult to compare to other results

  • Points used for alignment can affect performance

    • Not considerable for expected ASM precision


How reliable is the result

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How reliable is the result?


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