ViBe - a powerful technique for background detection and subtraction in video sequences

Executive summary

Description

ViBe is a powerful pixel-based technique that detects the background in video sequences. Many experiments have shown that it performs better than the state-of-the-art techniques known in the scientific literature. In addition the computational load is lower than simple background techniques implemented in commercial products. ViBe is the perfect solution for both software and hardware implementations.

Code and program for Windows and Linux

• A program for Windows and Linux. Download an archive zip archive [10 MB - updated on May 19, 2011] to use ViBe on Windows (or under Wine in Linux). Details on this page.
  The program allows you to: (1) save the result for your own images, (2) change the few parameters of ViBe to experiment with, and (3) reproduce our results.
• Linux: link a C/C++ object file to your own code. We provide the object (compiled) code of ViBe for non-commercial applications. Under Linux, download the 32 bits zip or compressed tar file, or the 64 bits zip or compressed tar file. Details on this page.

Android

ViBe is also available as a demo application for android on Google Play (previously known as the Android Market).

Licensing opportunities

ViBe is protected by several patents (patent track: WO2009007198 / Publication date: 2009-01-15; Priority number(s): EP20070112011 20070708) / US (granted): US 8009918 B2 (pdf) / Japan (granted): JP 2011 4699564 B2
The University of Liege holds all the rights on the technology and the innovations have been validated during the patent track.

Commercial license

For licensing the technology, please contact Prof. Van Droogenbroeck or Mr. Van der Elstraeten.

Evaluation license

We propose an evaluation license that includes the full source of the application provided on this site [see download page], plus the documentation and instructions to build the program, and another version of the same application with many optimizations (about 5 times faster than the original version).

Major advantages:

• Very low computational load. Operations are limited to subtractions and operations on memory blocks. A downscaled version only needs one comparison per pixel and one byte of memory per pixel (see illustration below).
• Parameter-free method. There is no need to adapt parameter values to the content. Absolutely all the experiments have been led with the same set of values.
• Ready for direct inclusion in commercial products. Suited both for software and hardware inclusions.
• Faster and improved performances in comparison with state-the-art techniques (Mixture of Gaussians, Parametric methods, Sacon, etc).
• Pixel-based technique, ideal for any pre-processing step. ViBe allows you to model the objects in the videos as you like.
• Instantaneous initialization of the background model. ViBe is ready to operate from the second frame of any video sequence.
• Robust to noise.

References

• O. Barnich and M. Van Droogenbroeck. ViBe: A universal background subtraction algorithm for video sequences. In IEEE Transactions on Image Processing, 20(6):1709-1724, June 2011. Also available on the University site in PDF format: , and HTML format. This paper contains a very detailed pseudo-code description of the complete algorithm.
• M. Van Droogenbroeck and O. Paquot. Background Subtraction: Experiments and Improvements for ViBe. In Change Detection Workshop (CDW), Providence, Rhode Island, June 2012. Available on the University site in PDF format: , and HTML format.
• O. Barnich and M. Van Droogenbroeck. ViBe: a powerful random technique to estimate the background in video sequences. In International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009), pages 945-948, April 2009. Available as a IEEE publication or on the University site.
• Patent description at the "freepatentsonline" web site

Performance

• An independant evaluation is available in S. Brutzer, B. Hoferlin, and G. Heidemann. Evaluation of background subtraction techniques for video surveillance. In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pages 1937-1944, Colorado Spring, USA, June 2011.
  In their conclusions, they claim: "Considering these aspects, Barnich is a strong favorite, since it is simple and almost parameterless."
• See the changedetection website for a comparative benchmarking of ViBe and ViBe+ on 31 sequences. Please note that ViBe+ has the best precision of all the techniques!

Contacts

For any question, please contact Prof. Van Droogenbroeck .
See also the site of the Interface, in charge of the partnerships between companies and the University of Liege.

ViBe inside a digital camera

Illustrations for a static camera

View from the roof of a house

Illustrations for a moving camera

Global and local motions are estimated via optical flow on a pre-defined grid of pixels [preliminary work].

Camera in motion