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A PERCEPTUAL INTERFACE USING INTEGRAL PROJECTIONS

A PERCEPTUAL INTERFACE USING INTEGRAL PROJECTIONS. Ginés García Mateos ginesgm@um.es Sergio Fructuoso Muñoz sergiofr@ono.com Dept. de Informática y Sistemas University of Murcia - SPAIN. System overview. Face detector and tracker. Camera. User of the per-ceptual interface.

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A PERCEPTUAL INTERFACE USING INTEGRAL PROJECTIONS

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  1. A PERCEPTUAL INTERFACE USING INTEGRAL PROJECTIONS Ginés García Mateos ginesgm@um.es Sergio Fructuoso Muñoz sergiofr@ono.com Dept. de Informática y Sistemas University of Murcia - SPAIN

  2. System overview Face detector and tracker Camera User of the per-ceptual interface MOVEFORWARD/BACKWARDLEFT/RIGHT ROTATE LEFT/RIGHT LOOKUP/DOWN FACE LOCATION:X: 6 Y: 0 Z: 3 FACE ORIENTATION: Roll: 7.7 Pitch: 0 Yaw: 3 FACE MOVEMENT:ΔX: -2 ΔY: 1 ΔZ: 0 3D movement and pose estimation Control signals (virtual world movement) Virtual world rendering

  3. Face integral projections • Definition. Let i(x,y) be an image, and R(i) a region in it: Vertical Integral Projection Horizontal Integral Projection PVR : {ymin, ..., ymax}  R PHR : {xmin, ..., xmax}  R PVR(y) = i(x,y);  (x,y)  R(i) PHR(x) = i(x,y);  (x,y)  R(i) • When applied to human faces, typical patterns of projection appear. • This is used to design a face detector and tracker. Pv(y): Vertical I.P. of the face Ph1(y): Horizon-tal I.P. of eyes’ region Ph2(y): Horizon-tal I.P. of mouth’s region

  4. Face tracking with I.P. Face tracking is a 3-step process. 1. Vertical alignment: compute move-ment and scale in vertical direction 2. Horizontal alignment: compute move-ment and scale in horizontal direct. 3. Orientation alignment: compute orienta-tion of the face Green line:Projection modelRed line:Projection instance • FACE PVFACE(y) Align PVFACE STEP 1 y y Align PHEYES PHEYES(x) EYES STEP 2 x x Align PVEYEi PVEYE1,PVEYE2 EYE1, EYE2 STEP 3 • y • y

  5. Pose estimation (i) • Depth estimation: inversely proportional to the size of the head in the image. Approximated with the eye-to-eye distance. Relative distances 0.674 0.947 1.184 1.636 • Roll estimation: approximated with the perceived angle of the eyes. Roll angles -33.4º -13.0º 13.5º 20.2º

  6. Pose estimation (ii) • Pitch estimation: a heuristic measure is defined, using the vertical I.P. of the face Estimated pitch 19 -2 -9 • Yaw estimation: another heuristic, using the horizontal I.P. of the eyes. Estimated yaw -7 0 11

  7. Virtual environment • The perceptual interface is used to control the movement in a virtual 3D world. • We have used DirectX 9 and OpenCV 3. Virtual 3D world

  8. Results and conclusion • Sample videos available at:http://dis.um.es/~ginesgm/fip/percint.html Conclusions • Depth and roll estimation is very reliable. • Pitch and yaw are less stable.  .. ,10/2004

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