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Brief Description

The Neuromorphic-Caltech101 (N-Caltech101) dataset is a spiking version of the original frame-based Caltech101 dataset. The original dataset contained both a "Faces" and "Faces Easy" class, with each consisting of different versions of the same images. The "Faces" class has been removed from N-Caltech101 to avoid confusion, leaving 100 object classes plus a background class. The N-Caltech101 dataset was captured by mounting the ATIS sensor on a motorized pan-tilt unit and having the sensor move while it views Caltech101 examples on an LCD monitor as shown in the video below. A full description of the dataset and how it was created can be found in the paper below. Please cite this paper if you make use of the dataset.
  • Orchard, G.; Cohen, G.; Jayawant, A.; and Thakor, N.  “Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades"Frontiers in Neuroscience, vol.9, no.437, Oct. 2015 (open access Frontiers link)


The data is available for download below:
Matlab and Python code for reading and working with the datasets is available on the code page.

Each example is a separate binary file consisting of a list of events. Each event occupies 40 bits as described below:
  • bit 39 - 32: Xaddress (in pixels)
  • bit 31 - 24: Yaddress (in pixels)
  • bit 23: Polarity (0 for OFF, 1 for ON)
  • bit 22 - 0: Timestamp (in microseconds)

The videos below show the conversion process in action and some of the resulting recordings.

Recording Setup

N-Caltech 101 examples