Instrumentation & Measurement Magazine 23-8 - 20

Fig. 2. Polarimetric Dynamic Vision Sensor p(DVS) principles.

can trigger events independently of the other pixels in the
DVS 128's sensor. As a result, the DVS 128 does not record in a
video format such as AVI. The DVS 128 produces recordings in
the form of AEDAT (Address Event Data) files, the format of
which will be discussed later.
The composite target system consists of a set of Thor Labs
chopper wheels. The wheel closest to the DVS128 is a MC1F2
2-slot chopper wheel (referred to as the modulator) which
is driven by a New Focus 3501 Optical Chopper. The second
wheel is a MC1F10 10-slot chopper wheel (referred to as the
target) which is placed directly behind the modulator and remains stationary for the duration of this study. The target is
illuminated through an LED light source to improve visibility.
A white polyurethane background is placed behind the target system.
For this study, recordings were taken at six different chopping frequencies set by the New Focus 3501 Optical Chopper:
8 Hz, 10 Hz, 12 Hz, 14 Hz, 16 Hz and 18 Hz. However, the AEDAT files generated from the DVS128 are not immediately
suitable for neural networks due to their format. These AEDAT
20	

files must be transformed into a format that can be more easily
processed by a neural network. To achieve this, a custom program was made to transform AEDAT files into a CSV format
that displays event information as a series of time windows
containing the number of events that occurred in that time
window. Each configuration was recorded for 15 minutes and
then converted to CSV files. The CSV files contain three columns: OFF events, ON events and BOTH event counts, within
the time frame.
Using the number of events instead of full-frame images,
in each time window, significantly reduces the size of AEDAT recording to 24 bytes/time windows. In contrast, each
video-frame reconstructed from the DVS 128 sensor was approximately 2.3 kB.
There are two ways to reconstruct the AEDAT file as a CSV
file. Time-based reconstruction creates a frame for a specified
amount of time passed. Event-based reconstruction creates a
frame for when a specified number of events have occurred.
Event-based reconstructions lead to uneven time slices. For
this reason, time-based reconstruction was chosen because

IEEE Instrumentation & Measurement Magazine	

November 2020



Instrumentation & Measurement Magazine 23-8

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