Research Projects (2008)
- Show Keywords
- 3D Computer Vision 3D reconstruction Aerial Vision Augmented Reality Augmented Video Best Paper Award Biometrics Caleydo Computer Graphics Computer Vision Convex Optimization Coordinate transformations detection face Fingerprint Georeferencing GPU GUI HOG Human Computer Interaction Image Labelling Industrial Applications Information Visualization integral imaging Interaction Interaction Design Machine Learning Medical computer vision Medical Visualization Mixed Reality Mobile computing Mobile phone Model Multi-Display Environments Multiple Perspectives Object detection Object recognition Object reconstruction Object Tracking On-Line Learning Robotics Segmentation Shape analysis shape from focus SLAM Software Projects Structure from Motion Surveillance SVM Symmetry Tracking Fusion Tracking, Action Recognition User Interfaces Variational Methods Virtual reality and augmented reality Visual Tracking Visualization
Christian Doppler Laboratory for Handheld Augmented Reality
Augmented Reality (AR) combines real and virtual in a single view, putting information right were it belongs - into the real world. AR is still a young research field and hence strongly driven by basic research and experimental methods, while only few successful commercial applications have been deployed. One of the reasons is that past hardware (such as head-mounted displays and Tablet PCs) have not been sufficiently inexpensive and ergonomically satisfactory. Therefore, recent AR research shows a trends towards deploying AR on advanced mobile phones, using the phone camera as video see-through interface for a “magic lens” style of AR. Recent research in the proposer’s group has first the first time established a baseline technology for achieving real-time performance AR on mobile phones, and this development has been meet with great interest from industry. This proposal the logical consequence of this development. It is concerned with extending this research in several directions, in particular making techniques more scalable (sometimes several orders of magnitude), so that realistic real world scenarios interesting for commercial applications can be attacked by industry. Firstly, we want to expand our real-time computer-vision based pose tracking and object recognition techniques. Secondly, we propose to develop realistic AR image synthesis and visualization methods. Thirdly, we suggest an investigation into efficient 3D interaction techniques with and for AR phones. Finally, we suggest the creation of a distributed infrastructure based on Web 2.0 technology for scalable content creation and deployment of geo-referenced AR applications on phones.