1 / 10

Face Detection Project

Face Detection Project. Nitin Kartik nitin.kartik@motorola.com EE368 Group 24 Spring 2002, Stanford University Prof. Bernd Girod. Algorithm Design. Seconds. 15. Sub-Sample Color Rejection Black-and-White Correlation Coefficient Centroids. 2. 2. 52. 1. Step 1: Sub-sample.

hastin
Download Presentation

Face Detection Project

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Face Detection Project • Nitin Kartiknitin.kartik@motorola.com • EE368 Group 24 • Spring 2002,Stanford University • Prof. Bernd Girod 1

  2. Algorithm Design Seconds 15 • Sub-Sample • Color Rejection • Black-and-White • Correlation Coefficient • Centroids 2 2 52 1 2

  3. Step 1: Sub-sample • 10x10 Reduction • Averaging over pixels(Uniform Filter) • Reduce Processing 3

  4. Step 2: Color Rejection • Trained from Examples • Color Ratios • Min/Max Table Ratio Min Max Red : Green 1.000 4.500 Green : Blue 0.843 12.000 Blue : Red 0.0185 1.000 4

  5. Step 3: Black-and-White • No need for Color any more • Average Red, Green, Blue Components • Further Reduce Processing 5

  6. Step 4: Correlation Coefficient • Face Template (Averages) • Compute Pixel-wise Correlation Coefficient • Some Falsely Detected Faces 6

  7. Ideal Classifier Practical Classifier Face Face Non-Face Non-Face Threshold Threshold Step 4: Correlation Coefficient(False Alarms) • Practical Classifiers 7

  8. Step 5: Determine Centroids • Hunting Algorithm • Min / MaxWidth / Height • Centroid = (midX, midY) 8

  9. Discarded Alternatives • Sub-sampling with other factors • Erosion / Dilation • RMS-Based Rejection 9

  10. Face Detection Project • Nitin Kartiknitin.kartik@motorola.com • EE368 Group 24 • Spring 2002,Stanford University • Prof. Bernd Girod 10

More Related