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Elliptical Head Tracking Using Intensity Gradients and Color Histograms

Elliptical Head Tracking Using Intensity Gradients and Color Histograms. Stan Birchfield Stanford University Autodesk Advanced Products Group http://vision.stanford.edu/~birch. PROBLEM. ZOOM. TILT. PAN. APPLICATIONS: * video conferencing * distance learning. CHALLENGES:

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Elliptical Head Tracking Using Intensity Gradients and Color Histograms

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  1. Elliptical Head Tracking Using Intensity Gradients and Color Histograms Stan Birchfield Stanford University Autodesk Advanced Products Group http://vision.stanford.edu/~birch

  2. PROBLEM ZOOM TILT PAN APPLICATIONS: * video conferencing * distance learning CHALLENGES: * rotation * multiple people * zoom

  3. PREVIOUS METHODS OUT-OF-PLANE ROTATION ARBITRARY CAMERA MOVEMENT Criterion MULTIPLE MOVING PEOPLE FLESH- COLORED OBJECTS Method 1. TEMPLATE [Hager & Belhumeur, 1996] N Y Y Y 2. FLESH COLOR [Fieguth & Terzopoulos, 1997] N N N Y 3. BACKGROUND DIFFERENCING [Graf et al., 1996] Y Y N N

  4. INTENSITY EDGES • DEPTH & MOTION . DISCONTINUITIES COMPLEMENTARY CRITERIA INTERIOR BOUNDARY CUES: • COLOR • MOTION • TEXTURE

  5. GEOMETRIC: 1. Nearly rigid 2. Nearly ellipsoid Easy to model WHY FOCUS ON THE HEAD? APPLICATION: 1. Interesting, useful 2. Well-connected to other body parts

  6. LOCAL HEAD SEARCH Ellipse: vertical aspect ratio = 1.2 state s = (x,y,s) s HEADMODEL (x,y) SEARCH GRADIENT COLOR SEARCH RANGE velocity prediction

  7. GRADIENT MODULE TWO CHOICES: 1. MAGNITUDE 2. DOT PRODUCT ellipse normal gradient NORMALIZATION

  8. COLOR MODULE B+G+R (4 bins) COLOR SPACE B-G (8 bins) G-R (8 bins) HISTOGRAM INTERSECTION [Swain & Ballard 1991] SKIN HAIR MODEL CURRENT INTERSECTION NORMALIZATION

  9. SUMMARY OF ALGORITHM OFF-LINE: 1. Manually place head within ellipse 2. Store model histogram RUN TIME: 1. At each hypothesized location, compute - Sum of gradient around perimeter - Histogram intersection 2. Move ellipse to location that maximizes sum of two criteria

  10. Controls pan, tilt, zoom Handles textured backgrounds More robust Large basin of attraction Controls pan, tilt Keeps off neck Scale in front of flesh-colored object Scale when back turned COMPARISON OF MODULES GRADIENT COLOR

  11. BASIN OF ATTRACTION Gradientconfused, pulls to left Colorpulls to right

  12. COMPUTING TIME (on a 200 MHz Pentium Pro) Real time (30 Hz) Computing time per frame (ms) Search range

  13. CONCLUSION SUCCESSES: 1. Tracks head in real time on standard hardware 2. Insensitive to - full 360-degree out-of-plane rotation - arbitrary camera movement (including zoom) - multiple moving people - severe but brief occlusion - hair/skin color, hair length, facial hair, glasses FUTURE WORK: 1. Speed (computer speed and NTSC video standard) 2. Color adaptation, but imprecise localization 3. No explicit model of occlusion

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