1 / 15

Announcements

Announcements. Project 3 out today demo session at the end of class. Photometric Stereo. Readings Forsyth and Ponce, section 5.4 online: http://www.cs.berkeley.edu/~daf/bookpages/pdf/chap05-final.pdf. Merle Norman Cosmetics, Los Angeles. image intensity of P. Diffuse reflection.

ranee
Download Presentation

Announcements

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. Announcements • Project 3 out today • demo session at the end of class

  2. Photometric Stereo • Readings • Forsyth and Ponce, section 5.4 • online: http://www.cs.berkeley.edu/~daf/bookpages/pdf/chap05-final.pdf Merle Norman Cosmetics, Los Angeles

  3. image intensity of P Diffuse reflection • Simplifying assumptions • I = Re: camera response function f is the identity function: • can always achieve this in practice by solving for f and applying f -1 to each pixel in the image • Ri = 1: light source intensity is 1 • can achieve this by dividing each pixel in the image by Ri

  4. Shape from shading • Suppose • You can directly measure angle between normal and light source • Not quite enough information to compute surface shape • But can be if you add some additional info, for example • assume a few of the normals are known (e.g., along silhouette) • constraints on neighboring normals—“integrability” • smoothness • Hard to get it to work well in practice • plus, how many real objects have constant albedo?

  5. L3 L2 L1 Photometric stereo N V • Can write this as a matrix equation:

  6. Solving the equations

  7. Least squares solution: • Solve for N, kd as before What’s the size of LLT? More than three lights • Get better results by using more lights

  8. call this J Color images • The case of RGB images • get three sets of equations, one per color channel: • Simple solution: first solve for N using one channel • Then substitute known N into above equations to get kd s:

  9. Computing light source directions • Trick: place a chrome sphere in the scene • the location of the highlight tells you where the light source is

  10. Recall the rule for specular reflection • For a perfect mirror, light is reflected about N • We see a highlight when V = R • then L is given as follows:

  11. Computing the light source direction • Can compute N by studying this figure • Hints: • use this equation: • can measure c, h, and r in the image Chrome sphere that has a highlight at position h in the image N h H rN c C sphere in 3D image plane

  12. V2 V1 N Depth from normals • Get a similar equation for V2 • Each normal gives us two linear constraints on z • compute z values by solving a matrix equation (project 3)

  13. Project 3

  14. Limitations • Big problems • doesn’t work for shiny things, semi-translucent things • shadows, inter-reflections • Smaller problems • camera and lights have to be distant • calibration requirements • measure light source directions, intensities • camera response function

  15. Trick for handling shadows • Weight each equation by the pixel brightness: • Gives weighted least-squares matrix equation: • Solve for N, kd as before

More Related