Title: Perspective Structure from Motion
1PerspectiveStructure from Motion
2Orthographic ? Perspective
- Last time, considered weak perspective
- With full perspective, can recover more
information (translation along optical axis) - Result can recover geometry and full motion up
to global scale factor
3Perspective SFM Methods
- Bundle adjustment (full nonlinear minimization)
- Methods based on factorization
- Methods based on fundamental matrices
- Methods based on vanishing points
4Motion Field for Camera Motion
- Translation
- Motion field lines converge (possibly at ?)
5Motion Field for Camera Motion
- Rotation
- Motion field lines do not converge
6Motion Field for Camera Motion
- Combined rotation and translationmotion field
lines have component that converges, and
component that does not - Algorithms can look for vanishing point,then
determine component of motion around this point - Focus of expansion / contraction
- Instantaneous epipole
7SFM Algorithm
- Compute optical flow
- Find vanishing point (least squares solution)
- Find direction of translation from epipole
- Find perpendicular component of motion
- Find velocity, axis of rotation
- Find depths of points (up to global scale)
8Shape from Shading and Texture
9Lambertian Reflectance Model
- Diffuse surfaces appear equally bright from all
directions - For point illumination, brightness proportional
to cos q
10Lambertian Reflectance Model
- Therefore, for a constant-colored object with
distant illumination, can write E L r l?nE
observed brightnessL brightness of light
sourcer reflectance (albedo) of surfacel
direction to light sourcen surface normal
11Shape from Shading
- The above equation contains some information
about shape, and in some cases is enough to
recover shape completely(in theory) if Lr and l
are known - Similar to integration (surface normal is like a
derivative), but only know a part of derivative - Have to assume surface continuity
- No solution in the presence of noise
12Variational Shape from Shading
- Approach energy minimization
- Given observed E(x,y), find shape z(x,y)that
minimizes energywhere
13Variational Shape from Shading
- Solve by techniques from calculus of variations
- Use Euler-Lagrange equations to get a PDE, solve
numerically - Unlike with snakes, greedy methods tend not to
work
14Difficulties with Shape from Shading
- How to find L, r, l?
- Estimate based on scene statistics
- Shadows
- Non-Lambertian (e.g., specular) surfaces
- More than 1 light, or diffuse illumination
- Interreflections
15Shape from Shading Results
Trucco Verri
16Shape from Shading Results
17Active Shape from Shading
- Idea several (user-controlled) light sources
- More data
- Allows determining surface normal directly
- Allows spatially-varying reflectance
- Redundant measurements discard shadows and
specular highlights - Often called photometric stereo
18Photometric Stereo Setup
Rushmeier et al., 1997
19Photometric Stereo Math
- For each point p, can write
- Constant a incorporates light source brightness,
camera sensitivity, etc.
20Photometric Stereo Math
- Solving above equation gives (r /a) n
- n must be unit-length ? uniquely determined
- Determine r up to global constant
- With more than 3 light sources
- Discard highest and lowest measurements
- If still more, solve by least squares
21Photometric Stereo Results
Recovered normals (re-lit)
Inputimages
Recovered color
Rushmeier et al., 1997
22Texture
- Texture repeated pattern on a surface
- Elements (textons) either identical or come
from some statistical distribution - Shape from texture comes from looking at
deformation of individual textons or from
distribution of textons on a surface
23Shape from Texture
- Much the same as shape from shading, but have
more information - Foreshortening gives surface normal (not just
one component, as in shape from shading) - Perspective distortion gives information about
depth directly - Sparse depth information (only at textons)
- About the same as shape from shading, because of
smoothness term in energy eqn.
24Shape from Texture Results
Forsyth