BRISK: Binary Robust Invariant Scalable Keypoints



Focus-Project SCALEVO wins Gold Award at iCreateStudent Innovation Challenge


Kollege Roboter? «Der Mensch ist noch weit überlegen» - Interview von Roland Siegwart auf SRF Online Portal (in German)


Autonomous Cars – Talk with Roland Siegwart (in German) 13.08.2015


Focus-Project SCALEVO wins National Instruments Global Student Design Award


ICAR Best Paper Award


ASL's AtlantikSolar UAV breaks world endurance record with 81 hour flight


The V-Charge project concludes its four year runtime with an extensive three-week long demonstration


S.Lynen, M.Bosse, R.Siegwart co-authored RSS paper became finalist for the Best SystemsPaper Award


ASL’s AtlantikSolar UAV achieves 28-hourfully-solar powered day/night flight


Marcin Dymczyk was awarded with the ETH Medal for his Master Thesis


Dr. K. Alexis: Assistant Professor in Computer Science & Engineering at the University of Nevada 


Mina Kamel awarded the Willi-Studer Preis as best Master's Degree in RSC


Autonomous cars / V-Charge in print media


Pixelbots live in Spanish TV


Primary school students perform play with Robot "Igor"


AtlantikSolar research on Meteorological Path Planning(MeteoSwiss and ETHZ cooperation) wins two prizes


Today in 20min: "Rettungsroboter nach dem Vorbild der Natur"


Today: Public Defense S. Leutenegger & J. Maye at the bqm


K. Alexis won 2014 Premium Award for Best Paper in Control Theory & Applications


The SEPIOS Robot developed in our Focusproject won the NI Global Student Design Showcase 2014 in Austin Texas


"Best Robot Video" at the AAAI Video Competition for M. Hutter, M. Hoepflinger, C. Gehring, M. Bloesch, M. Kolbe, R. Siegwart


“Success Stories” on the SPARC - The Partnership for Robotics in Europe - website. Check them out!


The paper from G. Darivianakis, K. Alexis, M. Burri and R. Siegwart on "Hybrid Predictive Control for Aerial Robotic Physical Interaction towards Inspection Operations" finalisted for the Best Automation Paper Award on ICRA 2014, Hong Kong.


StarlETH andVelociRoACH featured in IEEE Spectruma


MasterAwards for M. Bürki, J. Hwangbo and R. Khanna


ASL sends two focus teams to the rollout presentation on 27th May


J. Alonso-Mora, R. Siegwart, P. Beardsley win Best Video Award (2nd Price) in the 9th ACM/IEEE Int. Conf. in Human-Robot Interaction (HRI 2014)!


Marco Hutter wins ETH Medal for his Doctoral Thesis "StarlETH & Co. - Design and Control of Legged Robotics with Compliant Actuation"


Davide Scaramuzza - UniZH - formerly at ASL won IEEE RAS (Robotics and Automation Society) Early Career Award


Roland Siegwart - ETH Zurich, Switzerland IEEE won Inaba Technical Award for Innovation Leading to Production


News Archive

Effective and efficient generation of keypoints from an image is a well-studied problem in the literature and forms the basis of numerous Computer Vision applications. Established leaders in the field are the SIFT and SURF algorithms which exhibit great performance under a variety of image transformations, with SURF in particular considered as the most computationally efficient amongst the high-performance methods to date.

We propose BRISK, a novel method for keypoint detection, description and matching. A comprehensive evaluation on benchmark datasets reveals BRISK's adaptive, high quality performance as in state-of-the-art algorithms, albeit at a dramatically lower computational cost (an order of magnitude faster than SURF in cases). The key to speed lies in the application of a novel scale-space FAST-based detector in combination with the assembly of a bit-string descriptor from intensity comparisons retrieved by dedicated sampling of each keypoint neighborhood.

Demo Video

Watch BRISK in action.

ICCV 2011 Paper

Stefan Leutenegger, Margarita Chli and Roland Siegwart, BRISK: Binary Robust Invariant Scalable Keypoints, to appear in Proceedings of the IEEE International Conference on Computer Vision (ICCV) 2011.


Open-source package containing windows and linux libraries, a demo application, and a Matlab mex interface:

download (16 MB)
(v0.1 December 10th 2011)

Provided under the terms and conditions of the BSD license.

Please contact, if you have related questions or suggestions.


Wichtiger Hinweis:
Diese Website wird in älteren Versionen von Netscape ohne graphische Elemente dargestellt. Die Funktionalität der Website ist aber trotzdem gewährleistet. Wenn Sie diese Website regelmässig benutzen, empfehlen wir Ihnen, auf Ihrem Computer einen aktuellen Browser zu installieren. Weitere Informationen finden Sie auf
folgender Seite.

Important Note:
The content in this site is accessible to any browser or Internet device, however, some graphics will display correctly only in the newer versions of Netscape. To get the most out of our site we suggest you upgrade to a newer browser.
More information

© 2015 ETH Zurich | Imprint | Disclaimer | 11 December 2011