Course 16... Wide baseline VBR: Silhouettes and photo-consistency

Using visual hulls to extract 3D structure. Image-based vs. polyhedral visual hull ("VH").

Good ibvh example from high ring of cameras. Trick (2000 paper) to use scanline scanning to build image data structure for fast computation. pvh example shows rougher depth map.

Camera weighting: what to project onto geo: blend three nearest views, removing view with greatest disparity to ensure smooth transitions.

At this point we have a PowerPoint crash... summarizing w/o visual aid Conclusion: vh approach with camera weighing provides good results with a reasonable number of cameras.

Photo-consistency: plane-sweep: a multi-view stereo implementation. Compare cameras' reprojections onto planes at different depths-- depths appear sharp as plane intersects subject depth. Fast disparity computation-- sweep plane through depth, compute disparity, aggregate found depths. Use mipmap approach to eliminate multiple found depths per pixel in 2-camera case. Trivial to extend to more cameras.

Specular hilight problem: highlights and reflections interfere with matching. Enforcing photo-consistency works for this too-- uses least intense sample for texturing the point.