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Found 14 papers, 3 papers with code
Memory Efficient Corner Detection for Event-driven Dynamic Vision Sensors
In this paper, we propose a new event-driven corner detection implementation tailored for edge computing devices, which requires much lower memory access than luvHarris while also improving accuracy.
WaLiN-GUI: a graphical and auditory tool for neuron-based encoding
Neuromorphic computing relies on spike-based, energy-efficient communication, inherently implying the need for conversion between real-valued (sensory) data and binary, sparse spiking representation.
NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems
The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings.
Fast Trajectory End-Point Prediction with Event Cameras for Reactive Robot Control
Prediction skills can be crucial for the success of tasks where robots have limited time to act or joints actuation power.
Constraints on the design of neuromorphic circuits set by the properties of neural population codes
In the brain, information is encoded, transmitted and used to inform behaviour at the level of timing of action potentials distributed over population of neurons.
Braille Letter Reading: A Benchmark for Spatio-Temporal Pattern Recognition on Neuromorphic Hardware
Spatio-temporal pattern recognition is a fundamental ability of the brain which is required for numerous real-world activities.
PUCK: Parallel Surface and Convolution-kernel Tracking for Event-Based Cameras
Low latency and accuracy are fundamental requirements when vision is integrated in robots for high-speed interaction with targets, since they affect system reliability and stability.
LuvHarris: A Practical Corner Detector for Event-cameras
There have been a number of corner detection methods proposed for event cameras in the last years, since event-driven computer vision has become more accessible.
Closed-loop spiking control on a neuromorphic processor implemented on the iCub
In this paper, we present a closed-loop motor controller implemented on mixed-signal analog-digital neuromorphic hardware using a spiking neural network.
Exploiting Event Cameras for Spatio-Temporal Prediction of Fast-Changing Trajectories
This paper investigates trajectory prediction for robotics, to improve the interaction of robots with moving targets, such as catching a bouncing ball.
Audio-Visual Target Speaker Enhancement on Multi-Talker Environment using Event-Driven Cameras
In order to overcome this limitation, we propose the use of event-driven cameras and exploit compression, high temporal resolution and low latency, for low cost and low latency motion feature extraction, going towards online embedded audio-visual speech processing.
ATIS + SpiNNaker: a Fully Event-based Visual Tracking Demonstration
The Asynchronous Time-based Image Sensor (ATIS) and the Spiking Neural Network Architecture (SpiNNaker) are both neuromorphic technologies that "unconventionally" use binary spikes to represent information.
Event-based Vision: A Survey
Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur.
Independent Motion Detection with Event-driven Cameras
In this paper, we propose a method for segmenting the motion of an independently moving object for event-driven cameras.
