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Event Camera Characterization
Event cameras such as the Dynamic and Active Pixel Vision Sensor (DAVIS) are recent sensors with large potential for high-speed and high dynamic range robotic applications.
Event cameras such as the Dynamic and Active Pixel Vision Sensor (DAVIS, http://inilabs.com/products/dynamic-and-active-pixel-vision-sensor/ ) are recent sensors with large potential for high-speed and high dynamic range robotic applications. In spite the successful demonstration of the sensor to address several problems in computer vision and robotics, a comprehensive characterization of the sensor for such high level applications is still missing.
Event cameras such as the Dynamic and Active Pixel Vision Sensor (DAVIS, http://inilabs.com/products/dynamic-and-active-pixel-vision-sensor/ ) are recent sensors with large potential for high-speed and high dynamic range robotic applications. In spite the successful demonstration of the sensor to address several problems in computer vision and robotics, a comprehensive characterization of the sensor for such high level applications is still missing.
The goal of this project is to characterize various aspects of these novel types of sensors, such as: event noise characteristics (distribution and spectral density), contrast threshold (relation to bias settings, variability: spatially, with the pixel, and photometrically, with respect to the scene illumination), non-linearities, etc. Additionally, the images and IMU measurements provided by the DAVIS also require an integrated characterization. A successful completion of the project will lead to a better understanding of the potential, limitations and impact of these sensors on the design of novel algorithms for computer vision and robotics. The expected candidate should have a background on instrumentation, electrical engineering (to understand the principle of operation of the DAVIS pixels) and random processes. This project involves close collaboration with the Institute of Neuroinformatics (INI) at UZH-ETH.
The goal of this project is to characterize various aspects of these novel types of sensors, such as: event noise characteristics (distribution and spectral density), contrast threshold (relation to bias settings, variability: spatially, with the pixel, and photometrically, with respect to the scene illumination), non-linearities, etc. Additionally, the images and IMU measurements provided by the DAVIS also require an integrated characterization. A successful completion of the project will lead to a better understanding of the potential, limitations and impact of these sensors on the design of novel algorithms for computer vision and robotics. The expected candidate should have a background on instrumentation, electrical engineering (to understand the principle of operation of the DAVIS pixels) and random processes. This project involves close collaboration with the Institute of Neuroinformatics (INI) at UZH-ETH.
Guillermo Gallego (guillermo.gallego at ifi.uzh.ch)
Guillermo Gallego (guillermo.gallego at ifi.uzh.ch)