Event cameras such as the Dynamic Vision Sensor (DVS) are recent sensors with large potential for high-speed and high dynamic range robotic applications. Since their output is sparse traditional algorithms, which are designed for dense inputs such as frames, are not well suited. The goal of this project is explore ways to adapt existing deep learning algorithms to handle sparse asynchronous data from events. Applicants should have experience in C++ and python deep learning frameworks (tensorflow or pytorch), and have a strong background in computer vision.
Event cameras such as the Dynamic Vision Sensor (DVS) are recent sensors with large potential for high-speed and high dynamic range robotic applications. Since their output is sparse traditional algorithms, which are designed for dense inputs such as frames, are not well suited. The goal of this project is explore ways to adapt existing deep learning algorithms to handle sparse asynchronous data from events. Applicants should have experience in C++ and python deep learning frameworks (tensorflow or pytorch), and have a strong background in computer vision.
The goal of this project is explore ways to adapt existing deep learning algorithms to handle sparse asynchronous data from events.
The goal of this project is explore ways to adapt existing deep learning algorithms to handle sparse asynchronous data from events.