VEET Light-Source Demos
The following videos demonstrate how the right and left VEET temple arms’ ambient light sensors capture data on characteristics of light near the eye. These videos provide insight into how the VEET lux estimations perform in real-world, mix-lighting conditions. By observing transitions in lux values as scene lighting changes, the viewer can make a qualitative assessment of how smoothly the VEET handles dynamic lighting conditions.
As the wearer navigates different light settings, the videos overlay the values the VEET sensors are collecting:
- System Time: System time of the computer running the Python script when the video frame was processed; Displayed in white text at the top-center of the video.
- Capture Time: System time of the computer running the Python script when the sensor data from VEET was received.
- Epoch: VEET epoch time at sensor read.
- PHO Gain: Ambient Light Sensor (ALS) gain setting for Spectral Sensor (PHO).
- IR Gain: ALS gain setting for infrared (IR) channel.
- PHO Counts: ALS raw counts for PHO channel.
- IR Counts: IR raw counts from the PHO sensor.
- IR/VIS Ratio*: Infrared / visible light ratio, which determines which portion of the piecewise lux equation is being used to calculate lux.
- LUX: Illuminance in lux, output from VEET temple arm.
*The IR/VIS ratio is used to determine which portion of the piecewise lux equation is being used for the estimate; for example, IR/VIS > 1.7045 for the incandescent region (see VEET Ambient Light Sensor lux Characterization Whitepaper).
How the Videos Were Made
- The videos were recorded with a GoPro Hero Black 13 (standard lens) mounted to a GoPro Headstrap 2.0. The GoPro was angled to roughly approximate the wearer’s field of view.
- Left and right VEET temple arms were installed on an adult pair of compatible glasses frames.
- No spectral sensor was used; all overlay data was captured from the VEET temple arms.
- The VEET ambient light sensor data was collected with a Python script that polls each VEET temple arm with serial commands at an approximate 1.5 Hz sample rate. The Python script receives GoPro video feed via USB Open GoPro API commands and overlays the sensor data on the live video stream with Open CV Python library for real-time monitoring.
- After the video streaming was completed, the final video was saved as an .mp4 file.