4 papers
Event-Based Structured Light for Depth Reconstruction using Frequency Tagged Light Patterns
T. Leroux, S. -H. Ieng, R. Benosman
This paper presents a new method for 3D depth estimation using the output of an asynchronous time driven image sensor. In association with a high speed Digital Light Processing pro…
Event-Based Features Selection and Tracking from Intertwined Estimation of Velocity and Generative Contours
Laurent Dardelet, Sio-Hoi Ieng, Ryad Benosman
This paper presents a new event-based method for detecting and tracking features from the output of an event-based camera. Unlike many tracking algorithms from the computer vision…
When Conventional machine learning meets neuromorphic engineering: Deep Temporal Networks (DTNets) a machine learning frawmework allowing to operate on Events and Frames and implantable on Tensor Flow Like Hardware
Marco Macanovic, Fabian Chersi, Felix Rutard +2
We introduce in this paper the principle of Deep Temporal Networks that allow to add time to convolutional networks by allowing deep integration principles not only using spatial i…
Real-time high speed motion prediction using fast aperture-robust event-driven visual flow
Himanshu Akolkar, SioHoi Ieng, Ryad Benosman
Optical flow is a crucial component of the feature space for early visual processing of dynamic scenes especially in new applications such as self-driving vehicles, drones and auto…