Our team of the ICG will attend with 14 people. Even I am already having a large number of appointments, I am happy to meet up with you. Just email me!
SSTT NFT is one of the tracking modules in SSTT core. Originally SSTT was conceived to replace the venereal ARToolkit as the standard tracker in osgART. Hence, the original implementation did only consider marker tracking but already abstracted tracking targets, localization and tracking on a higher level. The video below shows a prototype of SSTT with natural feature tracking using a non-optimized SURF descriptor. Due to the rather heavy weight implementation of using SURF without additional optimizations this part is not viable for the mobile version of SSTT.
SSTT Simple Cube is a demonstrator application to test the feasibility of vision based Augmented Reality on a larger set of devices. The app itself is not doing anything exciting except that it was the first fast vision based AR demo on the Android Market.
SSTT visualizer is a viewer application for 3D models enabled with Augmented Reality. It demonstrates the capabilities of the SSTT library. SSTT visualizer augments rectangular symbols in the environment and can be used for a variety of application areas ranging from engineering to medical visualization where 3D prototypes need to be presented within the real environment.
SSTT mobile is a subset of SSTT core optimized for mobile devices. It currently supports only marker tracking, skin and face recognition. SSTT mobile can be used and deployed on a number of devices as listed below. SSTT mobile was originally developed for Windows Mobile 5 and 6 ported to Android, Maemo, iOS and Symbian. Only the iOS, Maemo and especially the Android port are being continued.
SSTT - (Simplified Spatial Target Tracker) is a computer vision based tracking library for Augmented and Mixed Reality applications. It is a versatile and lean system suitable for desktop and embedded systems such as mobile phones. The basic variant implements numerous model based computer vision tracking algorithms with approaches ranging from traditional markers, ID based frames, rectangular textured targets to natural feature recognition (sometimes wrongly referred to as marker-less tracking). SSTT also allows for occlusion based interaction with tracking targets to provide higher interactivity in AR based user interfaces. Newer versions of SSTT add skin, face and shape recognition in order to make SSTT more versatile.
osgART is a cross platform toolkit for developing AR applications with the OpenSceneGraph API. osgART was invented by Julian Looser and then made by Raphael Grasset and Hartmut Seichter into a robust software framework with hundreds of useful features. The current working version is 2.x and is available from the osgART Website. osgART is been used in hundreds if not thousands of AR applications in research, education and commercial applications. It is most likely the most used open source AR application framework.
This was a consulting project for a company in the AR industry. The goal was to demonstrate the capabilities of SLAM based tracking even on rather low powered hardware. For this purpose a port of MiniPTAM targeting the N900 was created. The goal was to demonstrate if PTAM runs sufficiently fast on the N900 and optimized to the point of running at similar frame rates as on the iPhone. Additionally some effort was put into the project to paralellize the tracking to free up more time per frame for more advanced rendering and other interface enhancements.
PresentAR was developed to shorten the development cycle for AR based advertising. At that time desktop based novelty AR became quite popular and the HIT Lab NZ company, now Motim Technologies needed a quick way to satisfy their customers needs for presenting content such as animated characters, video and the like on tracking targets. Additionally, it was required that the application will have to run on Windows and Mac OS X. Based on that I developed PresentAR which is a conglomerate of OpenSceneGraph, osgART and wxWidgets hold together by a number of auxiliary libraries.
ComposAR is a framework for developing desktop Augmented Reality applications. The framework consist of a wrapper around OpenSceneGraph and osgART called osgSWIG. ComposAR allows to be adapted into a variety of end user application, spanning from a stand-alone editor and viewer up to an integrated system inside of Pure Data.
Benchworks is a collaborative Augmented Reality application that facilitates in-situ and remote collaboration on urban design proposals. Two users can seamlessly observe virtual and real objects for design purposes. The system was created to test the feasibility of Augmented Reality aided design collaborations in a studio setting.
sketchand+ is the outcome of my final Diplom project as an Architect with Specialization in CAAD at the Bauhaus University, Weimar. My vision was to integrate an emerging technology with the existing workflow in order to support the early stages of design, in particular sketching. Following through with this vision I developed a collaborative augmented reality application for sketching and formal investigation.
