OpenOF: Framework for Sparse Non-linear Least Squares Optimization on a GPU

Cornelius Wefelscheid, Olaf Hellwich
Computer Vision and Remote Sensing, Berlin University of Technology, Sekr. MAR 6-5, Marchstrasse 23, D-10587, Berlin, Germany
9th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), 2013

   title={Framework for Sparse Non-linear Least Squares Optimization on a GPU},

   author={Wefelscheid, Cornelius and Hellwich, Olaf},



Download Download (PDF)   View View   Source Source   Source codes Source codes




In the area of computer vision and robotics non-linear optimization methods have become an important tool. For instance, all structure from motion approaches apply optimizations such as bundle adjustment (BA). Most often, the structure of the problem is sparse regarding the functional relations of parameters and measurements. The sparsity of the system has to be modeled within the optimization in order to achieve good performance. With OpenOF, a framework is presented, which enables developers to design sparse optimizations regarding parameters and measurements and utilize the parallel power of a GPU. We demonstrate the universality of our framework using BA as example. The performance and accuracy is compared to published implementations for synthetic and real world data.
VN:F [1.9.22_1171]
Rating: 5.0/5 (1 vote cast)
OpenOF: Framework for Sparse Non-linear Least Squares Optimization on a GPU, 5.0 out of 5 based on 1 rating

* * *

* * *

Follow us on Twitter

HGPU group

1662 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

337 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: