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Statistical Approach to a Color-based F ace Detection Algorithm. EE 368 Digital Image Processing Group 15 Carmen Ng, Thomas Pun May 30, 2002. Statistical Approach to a Color-based Face Detection Algorithm. Assumptions 4 Stages: Pre-processing Skin Color Region Labeling

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statistical approach to a color based f ace detection algorithm

Statistical Approach to a Color-based Face Detection Algorithm

EE 368

Digital Image Processing

Group 15

Carmen Ng, Thomas Pun

May 30, 2002

statistical approach to a color based face detection algorithm
Statistical Approach to a Color-based Face Detection Algorithm
  • Assumptions
  • 4 Stages:
    • Pre-processing
    • Skin Color Region Labeling
    • Statistical Face Selection Techniques
    • Edge Detection
  • Advantages/Disadvantages
statistical approach to a color based face detection algorithm1
Statistical Approach to a Color-based Face Detection Algorithm

Assumptions:

  • Color image
  • Multiple faces with similar area
  • Face orientation
statistical approach to a color based face detection algorithm2
Statistical Approach to a Color-based Face Detection Algorithm

I . Image Pre-processing

  • Boundary extension
  • Improves accuracy
statistical approach to a color based face detection algorithm3
Statistical Approach to a Color-based Face Detection Algorithm

II . Skin Color Region Labeling

  • Color-based
    • Chrominance extraction in YCbCr space
  • Morphological operations
    • Dilation and erosion
slide6

<= Original Image

Rough Mask =>

statistical approach to a color based face detection algorithm4
Statistical Approach to a Color-based Face Detection Algorithm

III . Statistical Analysis

  • Popular area finder
    • Facial feature detector (holes in binary images)
    • Popular area, width and height
  • Face rejection
    • Reject unpopular areas
statistical approach to a color based face detection algorithm5
Statistical Approach to a Color-based Face Detection Algorithm

IV . Facial Feature (Eye) Detection

  • Approximate eye location
  • LPF to remove noise
  • Edge detection to locate strong edges
slide11

Typical Background

Typical Face

After LPF and Edge Detection

statistical approach to a color based face detection algorithm6
Statistical Approach to a Color-based Face Detection Algorithm

Results/Conclusions:

  • 88% success rate
  • Adv: fast, no training required,work with video compression std.
  • DisAdv: min of faces required in image, work best with reliable facial detector
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