Search Results for author:
Found 8 papers, 2 papers with code
Adaptive Global Decay Process for Event Cameras
To achieve this, at least one of three main strategies is applied, namely: 1) constant temporal decay or fixed time window, 2) constant number of events, and 3) flow-based lifetime of events.
A Framework for Event-based Computer Vision on a Mobile Device
We present the first publicly available Android framework to stream data from an event camera directly to a mobile phone.
Event-based Face Detection and Tracking in the Blink of an Eye
We will rely on a new feature that has never been used for such a task that relies on detecting eye blinks.
Event-Based Features Selection and Tracking from Intertwined Estimation of Velocity and Generative Contours
This paper presents a new event-based method for detecting and tracking features from the output of an event-based camera.
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
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 information but also increasingly large temporal window.
Real-time high speed motion prediction using fast aperture-robust event-driven visual flow
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 autonomous robots.
Time-to-Contact Map by Joint Estimation of Up-to-Scale Inverse Depth and Global Motion using a Single Event Camera
In this paper, we address the problem of time-to-contact (TTC) estimation using a single event camera.
An event-based implementation of saliency-based visual attention for rapid scene analysis
The saliency map model, originally developed to understand the process of selective attention in the primate visual system, has also been extensively used in computer vision.
