SSTT is a computer vision based tracking library for Augmented and Mixed Reality applications. It is similar to a marker based approach with a minimal set of constraints. Unlike similar libraries such as ARToolKit or StudierStube the approach of SSTT is not relying on chromatic or geometrical constraints. However, SSTT is also not a Natural Feature Tracking (NFT) library which are more complex and don’t yield a high robustness, speed or are depending on non-free algorithms. The SSTT tracking algorithm automatically qualifies various company logos or even images in books immediately tracking targets. The following video illustrates the SSTT tracking library.

Augmented Reality with SSTT from Hartmut Seichter on Vimeo.

osgSWIG on Windows in combination with wxPython

OpenSceneGraph implements a comprehensive scenegraph API for OpenGL. This project utilises SWIG to generate various bindings for Python, Ruby, Java and Lua. This toolkit came to live while working on various projects around AR and VR at the HITLabNZ. HITLabNZ agreed we need to involve more people and allowed me to open it up and I subsequently moved it into a repository on Google Code under the new name osgSWIG.

Using AR within a real urban design model

Benchworks is a collaborative Augmented Reality application to facilitate in-situ and remote collaboration on urban design proposals. Two users can seamlessly integrate and observe virtual and real objects.