Wednesday 30th January 2008, 4pm-5pm

Jean Ponce (ENS, INRIA Rocquencourt, France)

High-Fidelity Image-Based Modeling

Slides: not yet available
I will discuss some of our recent work on image-based modeling---that is, the process of acquiring geometric models of complex 3D objects and scenes from multiple images. I will first present a method for computing the visual hull of a solid bounded by a smooth surface, then carving it to recover concavities and optimize a global measure of photometric consistency. I will then discuss a new approach to multi-view stereopsis that outputs a (quasi) dense set of rectangular patches covering the surfaces visible in the input images. This algorithm does not require any initialization in the form of a bounding volume, and it detects and discards automatically outliers and obstacles. It does not perform any smoothing across nearby features, yet is currently the top performer in terms of both coverage and accuracy for four of the six Middlebury benchmark datasets. A simple but effective method for turning the resulting patch model into a mesh appropriate for image-based modeling is also presented. I will also discuss applications, and ongoing work on accurate camera calibration from stereo and motion capture from multiple, synchronized video streams. Finally, I will conclude with a brief overview of the Willow research activities.
Joint work with Yasutaka Furukawa at the University of Illinois at Urbana-Champaign.