Seth Hall
Mobile devices offer many new avenues for computer vision and in particular mobile augmented reality applications that have not been feasible with desktop computers. The motivation for this research is to improve mobile augmented reality applications so that natural features, instead of fiducial markers or pure location knowledge, can be used as anchor points for […]
View View   Download Download (PDF)   
Naoki Shibata, Shinya Yamamoto
With an aim to realizing highly accurate position estimation, we propose in this paper a method for efficiently and accurately detecting the 3D positions and poses of traditional fiducial markers with black frames in high-resolution images taken by ordinary web cameras. Our tracking method can be efficiently executed utilizing GPGPU computation, and in order to […]
Martin Knecht, Georg Tanzmeister, Christoph Traxler, Michael Wimmer
Recent methods in augmented reality allow simulating mutual light interactions between real and virtual objects. These methods are able to embed virtual objects in a more sophisticated way than previous methods. However, their main drawback is that they need a virtual representation of the real scene to be augmented in the form of geometry and […]
View View   Download Download (PDF)   
Jim Braux-Zin
State of the art Structure from Motion algorithms can produce a real-time sparse 3d map of the environment, in a fast, robust and efficient way. However, dense 3d maps would be very useful for accurate Augmented Reality with occlusion management. This project focus on generating accurate dense depth-maps in near real-time from the data provided […]
View View   Download Download (PDF)   
Takehiro Tawara, Kenji Ono
We propose a two-handed direct manipulation system to achieve complex volume segmentation of CT/MRI data in Augmented Reality with a remote controller attached to a motion tracking cube. At the same time segmented data is displayed by direct volume rendering using a programmable GPU. Our system achieves visualization of real time modification of volume data […]
View View   Download Download (PDF)   
Thomas Pintaric
This report describes a system that performs live-action compositing of physical and virtual objects to a panoramic background image in real-time at interactive rates. A static camera is directed towards a 40 cm3 miniature stage, whose backdrop has been colored in chromatic green. Users can add virtual objects and manipulate their parameters within the scene […]
View View   Download Download (PDF)   

* * *

* * *

Follow us on Twitter

HGPU group

1665 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

339 people like HGPU on Facebook

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2015 hgpu.org

All rights belong to the respective authors

Contact us: