Inter modality face sketch recognition
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Inter-modality Face Sketch Recognition. Hamed Kiani. Outline. Overview Previous Works Proposed Approach Results Summary. Overview. Face Recognition. Input Face. Known Face Images. Face Recognition System. Identity. Overview. Face sketch recognition. Verbal description. Viewing.

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Outline
Outline

  • Overview

  • Previous Works

  • Proposed Approach

  • Results

  • Summary

Inter-modality Face Sketch Recognition ICME'12


Overview
Overview

  • Face Recognition

Input Face

Known Face Images

Face Recognition System

Identity

Inter-modality Face Sketch Recognition ICME'12


Overview1
Overview

  • Face sketch recognition

Verbal description

Viewing

Drawing

Police artist

Sketch

Eyewitness

Known Face Photos

(Mug shot)

Photo-Sketch Matching

Suspect’s identity

Inter-modality Face Sketch Recognition ICME'12


Overview2
Overview

  • Modality Gap: the difference of visual cues between face sketch and photo.

Inter-modality Face Sketch Recognition ICME'12


Overview3
Overview

  • Visual cues of face come from:

    • Fine texture (appearance):

      low contrast details, flaws, moles, wrinkles , etc.

    • Coarse texture (shape):

      high contrast boundaries of facial components eyes, mouth, etc

Inter-modality Face Sketch Recognition ICME'12


Overview4
Overview

  • Face textures and modality gap:

  • Fine textures of a face photo captured by camera (true pixels)

  • Fine texture of a sketch is rendered by artist, depending on drawing style and tools

  • Fine textures of face photo and sketch are not equivalent: high amount of modality gap

  • Coarse texture (facial component and boundaries) exists in both sketch and photo

  • modality gap is not affected significantly by coarse texture

Inter-modality Face Sketch Recognition ICME'12


Proposed approach
Proposed Approach

  • Histogram of Averaged Oriented Gradients (HAOG): a modified version of Histogram of Oriented Gradients (HOG)

  • HOG for sketch recognition:

    Modeling local appearance and shape

    Based on fineand coarse textures.

    “Fine texture leads to a high amount of modality gap”

Inter-modality Face Sketch Recognition ICME'12


Proposed approach1
Proposed Approach

  • Idea of HAOG:

    Emphasizing coarse texture much more than fine texture in feature extraction.

  • How?

    By averagedgradient vector (dominant gradient) instead of pixel’s gradient vector (orientation and magnitude).

Inter-modality Face Sketch Recognition ICME'12


Proposed approach2
Proposed Approach

  • But: Local gradients cannot directly be averaged, opposite gradient vectors cancel each other

  • Solution: Doubling the angles of the gradient vectors before averaging: equal to squaring the length of gradient vectors [Bazen and Grez, 2002].

Inter-modality Face Sketch Recognition ICME'12


Proposed approach3
Proposed Approach

  • Thus, we define squared gradient vectors

Inter-modality Face Sketch Recognition ICME'12


Proposed approach4
Proposed Approach

  • HAOG

x-gradient

y-gradient

Inter-modality Face Sketch Recognition ICME'12


Proposed approach5
Proposed Approach

  • HAOG

HAOG

Inter-modality Face Sketch Recognition ICME'12


Proposed approach6
Proposed Approach

  • Given a query sketch and a gallery of face photos , face sketch recognition is done by:

: HAOG descriptor , :chi-square

Inter-modality Face Sketch Recognition ICME'12


Proposed approach7
Proposed Approach

Figure 1. (a1) Face photo, (a2) Face sketch, (b1,b2) Gradient magnitudes of (a1,a2), Squared gradient magnitudes of (a1,a2).

Inter-modality Face Sketch Recognition ICME'12


Proposed approach8
Proposed Approach

Figure 2. Face sketch (top), photo (bottom), (b,c,d) local patches (first row), HAOG descriptors (second row) and HOG descriptors (third row).

Inter-modality Face Sketch Recognition ICME'12


Results
Results

  • Results on CUHK dataset with 606 pairs of face photo/sketch

Inter-modality Face Sketch Recognition ICME'12


Summary
Summary

  • Face sketch recognition vs. face recognition

  • Modality gap

  • HOG vs. HAOG

  • Future work

Inter-modality Face Sketch Recognition ICME'12



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