  Acquiring 3D geometry of real world objects has various applications in 3D
digitization, such as navigation and content generation in virtual
environments. Image remains one of the most popular media for such visual tasks
due to its simplicity of acquisition. Traditional image-based 3D reconstruction
approaches heavily exploit point-to-point correspondence among multiple images
to estimate camera motion and 3D geometry. Establishing point-to-point
correspondence lies at the center of the 3D reconstruction pipeline, which
however is easily prone to errors. In this paper, we propose an optimization
framework which traces image points using a novel structure-guided dynamic
tracking algorithm and estimates both the camera motion and a 3D structure
model by enforcing a set of planar constraints. The key to our method is a
structure model represented as a set of planes and their arrangements.
Constraints derived from the structure model is used both in the correspondence
establishment stage and the bundle adjustment stage in our reconstruction
pipeline. Experiments show that our algorithm can effectively localize
structure correspondence across dense image frames while faithfully
reconstructing the camera motion and the underlying structured 3D model.
