Java tools for Address-Event Representation (AER) neuromorphic processing.

Permanent link: http://jaerproject.org

Welcome to the jAER Open Source Project Real time sensory-motor processing for event-based sensors and systems

Founded in 2007 to support event sensors and robot demonstrators developed by the Sensors Group, Inst. of Neuroinformatics, UZH-ETH Zurich.

You can find the latest releases at https://github.com/SensorsINI/jaer/releases.

Starting with jAER 2.0, (unsigned) binary installers are now available thanks to the multi-platform installer builder install4j.

Go to install4j jAER installers on dropbox to download installers. Windows: Click More info, Run anyway and Install anyway for unsigned app. MacOS: See opening unsigned dmg on MacOS. Right click, open with Archive Manager, and run the installer. Recommend to install to a user folder. Linux: Run the installer with sh <installer>.sh. Then you can jaer from the installation directory or gnome menu. See video installing and updating jaer on YouTube.

• install4j installers install a bundled version of the latest Java from Eclipse Adoptium (see Guide fo Java versions and features).
• Release install4j installers do NOT install git working copy, but using the new self-update feature introduced in jAER-1.8.1, you can initialize the release to a git working copy and pull+build within jAER.
• You will get the best experience running from lastest bug fixes.

• Download DVS128 data files from the DVS09 dataset and drop them onto the jAER window to play them with the DVS128 AEChip.
• Download DAVIS346 sample data files from the DAVIS24 dataset and drop them onto the jAER window to play them with the Davis346blue AEChip.

Systems built with Sensors Group chips:

• inilabs DVS128 DVS event camera and inivation DAVIS240, and DAVIS346 HVS cameras
• inilabs DAS (CochleaAMS) cochleas

Event cameras from others:

• iniVation Samsung DVExplorer

T. Delbruck, “Frame-free dynamic digital vision,” in International Symposium on Secure-Life Electronics, University of Tokyo, Mar. 2008, pp. 21–26. doi: 10.5167/uzh-17620. Available: http://dx.doi.org/10.5167/uzh-17620

jAER originally targetted characterization of Sensors Group event cameras and silicon cochleas, but has also been used to build many robots: robogoalie (code), audio localization by spike ITD (code), speaker identification from spiking cochlea (code), laser goalie (code), pencil balancer (code), bill (money) catcher (code), slot car racer (code), Dextra roshambo (rock-scissors-poaper) (code), incremental learning of new roshambo hand symbols (code). jAER was also used to develop many event camera algorithms: Feature extraction (code), tracking (code), optical flow methods (code), EDFLOW hardware optical flow (code), and efficient and accurate event denoising (code).

To develop with jAER, see the jAER User Guide gdoc.

Please use our GitHub bug tracker to report issues and bugs, or our Google Groups mailing list forum to ask questions.

• USER GUIDE: jAER User Guide gdoc
• VIDEO TUTORIALS: https://www.youtube.com/playlist?list=PLVtZ8f-q0U5hD9KOM4OZ1lixhwupj9uOm
• BUG TRACKER: https://github.com/SensorsINI/jaer/issues/
• USER FORUM: https://groups.google.com/d/forum/jaer-users/

See also

• DAVIS-USERS user forum: https://groups.google.com/forum/#!forum/davis-users
• inivation support pages: https://inivation.com/support/