2-D signal theoretic investigation of background elimination in visual tomographic reconstruction for safety and enabling health applications

Visual tomography is a relatively new method for 3D scene reconstruction. It is adopted from medical tomography and based on multiple images from different viewpoints of a scene. In this context, multidimensional spectra and filtering techniques are the key technology for the reconstruction process. Visual tomography differs from classical tomography in several aspects which leads to new challenges with respect to mathematical description. The present paper examines the influence of image background on reconstruction quality. This background problem does not appear in classical medical tomography applications. In particular, the influence of multidimensional sampling and restrictions with respect to the number of view angles can be analyzed by using multidimensional signal theoretical concepts. The differences between ideal (no background) and real acquisition conditions are examined. Visual tomography has the potential for innovative new fields of applications, where Enabling Technologies for Societal Challenges are the focus of our considerations. Demographic change leads to a high interest for enabling mobility for elderly people with physical disabilities. Walking frames equipped with such technologies will be able to assist such people in real day environments.