Research Projects (2002)

The scanning electron microscope (SEM) is an important tool to examine very small structures. Its large magnification combined with good contrast and large depth of view make it possible to view and characterize microscopic structures in the sub-micron scale. In the recent years, the problem of dense surface reconstruction from multiple SEM images was a research topic on this institute. Reconstruction approaches like shape from stereo and shape from photometric stereo have been evaluated. This work presents a framework for automatic scene reconstruction from three images acquired by a scanning electron microscope. The basic assumption is that the specimen is tilted eucentrically in front of the camera, camera geometry is assumed to be unknown but constant over all views. It is shown that methods for estimating the trifocal tensor as well as modern auto-calibration approaches can be adapted to the imaging conditions in the SEM, and Euclidean scene structure can be retrieved from three uncalibrated views. The performance of the proposed framework is evaluated on synthetic data as well as real images. It is shown that Euclidean scene structure can be retrieved robustly under varying image noise and inaccurate initialization.