Integrating Stereo and Shape from Shading

This paper presents a new method for integrating di erent low level vision modules, stereo and shape from shading, in order to improve the 3D reconstruction of visible surfaces of objects from intensity images. The integration process is based on correcting the 3D visible surface obtained from shape from shading using the sparse depth measurements from the stereo module by tting a surface into the di erence between the two data sets. A feedforward neural network is used to t a surface to the error di erence. An extended Kalman lter algorithm is used for the network learning. It is found that the integration of sparse depth measurements has greatly enhanced the 3D visible surface obtained from shape from shading in terms of metric measurements.

• Type: Conference
• Year: 1999
• Where: ICIP
• Authors: Mostafa G.-H. Mostafa, Sameh M. Yamany, Aly A. Farag
• Keywords: Error Di Erence, ICIP 1999, Image Processing, Sparse Depth Measurements, Visible Surface