Dense mirroring surface recovery from 1D homographies and sparse correspondences

In this work we recover the 3D shape of mirroring objects such as mirrors, sunglasses, and stainless steel objects. A computer monitor displays several images of parallel stripes, each image at a different angle. Reflections of these stripes in a mirroring surface are captured by the camera. For every image point, the directions of the displayed stripes and their reflections in the image are related by a 1D homography which can be computed robustly and using the statistically accurate heteroscedastic model, without monitor–image correspondence, which is generally required by other techniques. Focusing on a small set of image points for which monitor–image correspondence is computed, the depth and the local shape may be calculated relying on this homography. This is done by an optimization process which is related to the one proposed by Savarese, Chen and Perona[10], but is different and more stable. Then dense surface recovery is performed using constrained interpolation, which ...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Stas Rozenfeld, Ilan Shimshoni, Michael Lindenbaum
• Keywords: Computer Vision, CVPR 2007, Image, Image Points, Monitor–image Correspondence