CS654: Digital Image Analysis Lecture 8: Stereo Imaging.

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Presentation transcript:

CS654: Digital Image Analysis Lecture 8: Stereo Imaging

Recap of Lecture 7 Inverse perspective transformation and its issues Many to one mapping Generalized perspective transformation Fundamentals of camera calibration

Outline of Lecture 8 Fundamentals of stereo imaging Calculation of disparity Search space for point correspondence Correlation based correspondence

Camera calibration ….. (1) ….. (2) 6 pairs of points are required

Solving for unknowns

Perspective transformation World co-ordinate Image plane Two equations, three unknowns

Stereo geometry Image courtesy:

Introducing a second imaging plane Focal length of C1 Coordinate system for C1 Image point w.r.to C1 Coordinate system for C2 Image point w.r.to C2 Focal length of C2

Relationship between coordinate systems Coordinates of Camera #2 Rotation matrix Translation matrix Coordinates of Camera #1

Assumptions

Mathematical relationship between points For camera #1 For camera #2 Coordinate transformation is required

Rectified camera configuration Assume pure translation, without any rotation Lateral stereo geometry Axial stereo geometry

Modified camera configuration after lateral shift along x-axis LEFT RIGHT

Assumption

Mathematical relationship For camera #1 For camera #2 Incorrect

Solve for unknowns …….. (1) …….. (2) …….. (3) …….. (4)

Coordinate of the 3D world point Depth

Disparity

Search space for stereo matching LeftRight N N N N

Token Based Stereo Detect token Corners, interest point, edges Find correspondences Interpolate surface

Correlation Based Stereo Methods Depth is computed only at tokens and interpolated/ extrapolated to remaining pixel Disparity map is constructed based on a correlation measure

Correlation Based Stereo Methods Once disparity is available compute depth using Error Index of points

Thank you Next Lecture: Image Interpolation