Methodology for 3D scene reconstruction from digital camera images

Digital images provide today an important source of data that deserves a careful statistical analysis. This paper concerns methods for retrieval of 3D information, including shape and texture, from cheap digital camera imaging outputs. It includes a three step reconstruction of a 3D scene with texture, from arbitrary partial views, in absence of occlusions. In Patrangenaru and Patrangenaru [23], Mardia et. al. [20] and Patrangenaru and Mardia [24] a planar scene was reconstructed using image fusion, around representatives of sample mean projective shapes or sample mean affine shapes of landmark configurations shared by a number of partial views of the scene. In this paper we first analyze the advantages and limitations of such a reconstruction of a close to planar remote scene from its partial aerial views, by specializing this algorithm to affine transformations. Furthermore, we combine a projective shape reconstruction of a finite 3D configuration from its uncalibrated camera views, as developed in Patrangenaru, Liu and Sughatadasa [22], with a VRML technique, to reconstruct projectively a 3D scene with texture from a pair of digital camera images, thus allowing a more detailed statistical analysis of the scene pictured. We give three such examples of 3D reconstructions.