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Spatial convolution is arguably the most fundamental of 2D image processing operations. Conventional spatial image convolution can only be applied to a conventional image, that is, an array of pixel values (or similar image representation)…

Computer Vision and Pattern Recognition · Computer Science 2019-02-11 Cedric Scheerlinck , Nick Barnes , Robert Mahony

Event cameras encode visual information with high temporal precision, low data-rate, and high-dynamic range. Thanks to these characteristics, event cameras are particularly suited for scenarios with high motion, challenging lighting…

Computer Vision and Pattern Recognition · Computer Science 2020-12-10 Etienne Perot , Pierre de Tournemire , Davide Nitti , Jonathan Masci , Amos Sironi

The diffusion of drones presents significant security and safety challenges. Traditional surveillance systems, particularly conventional frame-based cameras, struggle to reliably detect these targets due to their small size, high agility,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Gabriele Magrini , Lorenzo Berlincioni , Luca Cultrera , Federico Becattini , Pietro Pala

We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low-latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Daniel Gehrig , Henri Rebecq , Guillermo Gallego , Davide Scaramuzza

Event cameras are bio-inspired vision sensors that naturally capture the dynamics of a scene, filtering out redundant information. This paper presents a deep neural network approach that unlocks the potential of event cameras on a…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Ana I. Maqueda , Antonio Loquercio , Guillermo Gallego , Narciso Garcia , Davide Scaramuzza

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time,…

In this paper we propose a method of corner detection for obtaining features which is required to track and recognize objects within a noisy image. Corner detection of noisy images is a challenging task in image processing. Natural images…

Computer Vision and Pattern Recognition · Computer Science 2012-09-14 Nilanjan Dey , Pradipti Nandi , Nilanjana Barman

Event cameras are a promising candidate to enable high speed vision-based control due to their low sensor latency and high temporal resolution. However, purely event-based feedback has yet to be used in the control of drones. In this work,…

Robotics · Computer Science 2020-03-31 Rika Sugimoto Dimitrova , Mathias Gehrig , Dario Brescianini , Davide Scaramuzza

Understanding human movement and city dynamics has always been challenging. From traditional methods of manually observing the city's inhabitant, to using cameras, to now using sensors and more complex technology, the field of urban…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Jack Brady , Andrew Dailey , Kristen Schang , Zo Vic Shong

Because of their high temporal resolution, increased resilience to motion blur, and very sparse output, event cameras have been shown to be ideal for low-latency and low-bandwidth feature tracking, even in challenging scenarios. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Nico Messikommer , Carter Fang , Mathias Gehrig , Giovanni Cioffi , Davide Scaramuzza

Visual object tracking under challenging conditions of motion and light can be hindered by the capabilities of conventional cameras, prone to producing images with motion blur. Event cameras are novel sensors suited to robustly perform…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Irene Perez-Salesa , Rodrigo Aldana-Lopez , Carlos Sagues

As the ubiquity of smart mobile devices continues to rise, Optical Camera Communication systems have gained more attention as a solution for efficient and private data streaming. This system utilizes optical cameras to receive data from…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Hang Su , Ling Gao , Tao Liu , Laurent Kneip

Unlike standard cameras that send intensity images at a constant frame rate, event-driven cameras asynchronously report pixel-level brightness changes, offering low latency and high temporal resolution (both in the order of micro-seconds).…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Valentina Vasco , Arren Glover , Elias Mueggler , Davide Scaramuzza , Lorenzo Natale , Chiara Bartolozzi

Event cameras are a new type of brain-inspired visual sensor with advantages such as high dynamic range and high temporal resolution. The geometric calibration of event cameras, which involves determining their intrinsic and extrinsic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Zibin Liu , Shunkun Liang , Banglei Guan , Dongcai Tan , Yang Shang , Qifeng Yu

This paper proposes a novel method for human hands tracking using data from an event camera. The event camera detects changes in brightness, measuring motion, with low latency, no motion blur, low power consumption and high dynamic range.…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Laura Duarte , Mohammad Safeea , Pedro Neto

Event cameras are a new type of image sensors that output changes in light intensity (events) instead of absolute intensity values. They have a very high temporal resolution and a high dynamic range. In this paper, we propose a method to…

Computer Vision and Pattern Recognition · Computer Science 2021-03-23 Hamid Sarmadi , Rafael Muñoz-Salinas , Miguel A. Olivares-Mendez , Rafael Medina-Carnicer

Event-based cameras, inspired by the biological retina, have evolved into cutting-edge sensors distinguished by their minimal power requirements, negligible latency, superior temporal resolution, and expansive dynamic range. At present,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Han Wang , Yuman Nie , Yun Li , Hongjie Liu , Min Liu , Wen Cheng , Yaoxiong Wang

This research project addresses the challenge of accurately tracking eye movements during specific events by leveraging previous research. Given the rapid movements of human eyes, which can reach speeds of 300{\deg}/s, precise eye tracking…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Chirag Seth , Divya Naiken , Keyan Lin

Event cameras, often referred to as dynamic vision sensors, are groundbreaking sensors capable of capturing changes in light intensity asynchronously, offering exceptional temporal resolution and energy efficiency. These attributes make…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Mira Adra , Simone Melcarne , Nelida Mirabet-Herranz , Jean-Luc Dugelay

In this work, we propose an edge detection algorithm by estimating a lifetime of an event produced from dynamic vision sensor (DVS), also known as event camera. The event camera, unlike traditional CMOS camera, generates sparse event data…

Robotics · Computer Science 2019-07-18 Sangil Lee , Haram Kim , H. Jin Kim