  Image-based 3D object modeling refers to the process of converting raw
optical images to 3D digital representations of the objects. Very often, such
models are desired to be dimensionally true, semantically labeled with
photorealistic appearance (reality-based modeling). Laser scanning was deemed
as the standard (and direct) way to obtaining highly accurate 3D measurements
of objects, while one would have to abide the high acquisition cost and its
unavailability on some of the platforms. Nowadays the image-based methods
backboned by the recently developed advanced dense image matching algorithms
and geo-referencing paradigms, are becoming the dominant approaches, due to its
high flexibility, availability and low cost. The largely automated geometric
processing of images in a 3D object reconstruction workflow, from
ordered/unordered raw imagery to textured meshes, is becoming a critical part
of the reality-based 3D modeling. This article summarizes the overall geometric
processing workflow, with focuses on introducing the state-of-the-art methods
of three major components of geometric processing: 1) geo-referencing; 2) Image
dense matching 3) texture mapping. Finally, we will draw conclusions and share
our outlooks of the topics discussed in this article.
