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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

Robot manipulation is a common task in fields like industrial manufacturing. Detecting when objects slip from a robot's grasp is crucial for safe and reliable operation. Event cameras, which register pixel-level brightness changes at high…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Thilo Reinold , Suman Ghosh , Guillermo Gallego

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, i.e., the Dynamic and Active-pixel Vision Sensor (DAVIS) ones, capture the intensity changes in the scene and generates a stream of events in an asynchronous fashion. The output rate of such cameras can reach up to 10 million…

Computer Vision and Pattern Recognition · Computer Science 2020-10-30 Sherif A. S. Mohamed , Jawad N. Yasin , Mohammad-Hashem Haghbayan , Antonio Miele , Jukka Heikkonen , Hannu Tenhunen , Juha Plosila

The use of video-imaging data for in-line process monitoring applications has become more and more popular in the industry. In this framework, spatio-temporal statistical process monitoring methods are needed to capture the relevant…

Applications · Statistics 2020-04-24 Hao Yan , Marco Grasso , Kamran Paynabar , Bianca Maria Colosimo

This paper investigates trajectory prediction for robotics, to improve the interaction of robots with moving targets, such as catching a bouncing ball. Unexpected, highly-non-linear trajectories cannot easily be predicted with…

Computer Vision and Pattern Recognition · Computer Science 2020-01-16 Marco Monforte , Ander Arriandiaga , Arren Glover , Chiara Bartolozzi

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a…

Robotics · Computer Science 2019-01-21 Elias Mueggler , Guillermo Gallego , Henri Rebecq , Davide Scaramuzza

Human pose estimation focuses on predicting body keypoints to analyze human motion. Currently, most pose estimation tasks rely on conventional RGB cameras. In contrast, event cameras provide high temporal resolution and low latency,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Haoxian Zhou , Chuanzhi Xu , Langyi Chen , Pengfei Ye , Haodong Chen , Yuk Ying Chung , Qiang Qu

Event cameras are bio-inspired sensors that perform well in challenging illumination conditions and have high temporal resolution. However, their concept is fundamentally different from traditional frame-based cameras. The pixels of an…

Computer Vision and Pattern Recognition · Computer Science 2022-06-13 Xin Peng , Ling Gao , Yifu Wang , Laurent Kneip

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 community, this process does not aim for particular…

Computer Vision and Pattern Recognition · Computer Science 2018-11-20 Laurent Dardelet , Sio-Hoi Ieng , Ryad Benosman

Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in static or low-motion scenes, rigidly mounted event cameras are unable to generate any events…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Vincenzo Polizzi , Stephen Yang , Quentin Clark , Jonathan Kelly , Igor Gilitschenski , David B. Lindell

Event-based cameras record an asynchronous stream of per-pixel brightness changes. As such, they have numerous advantages over the standard frame-based cameras, including high temporal resolution, high dynamic range, and no motion blur. Due…

Computer Vision and Pattern Recognition · Computer Science 2020-10-01 Dimche Kostadinov , Davide Scaramuzza

Event cameras have the ability to capture asynchronous per-pixel brightness changes, called "events", offering advantages over traditional frame-based cameras for computer vision applications. Efficiently coding event data is critical for…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Abdelrahman Seleem , André F. R. Guarda , Nuno M. M. Rodrigues , Fernando Pereira

Event cameras are bio-inspired vision sensors that asynchronously measure per-pixel brightness changes.The high-temporal resolution and asynchronicity of event cameras offer great potential for estimating robot motion states. Recent works…

Robotics · Computer Science 2025-01-07 Zhixiang Wang , Xudong Li , Yizhai Zhang , Panfeng Huang

Event cameras continue to attract interest due to desirable characteristics such as high dynamic range, low latency, virtually no motion blur, and high energy efficiency. One of the potential applications that would benefit from these…

Computer Vision and Pattern Recognition · Computer Science 2022-10-17 Tobias Fischer , Michael Milford

Event cameras are bio-inspired sensors that capture the per-pixel intensity changes asynchronously and produce event streams encoding the time, pixel position, and polarity (sign) of the intensity changes. Event cameras possess a myriad of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Xu Zheng , Yexin Liu , Yunfan Lu , Tongyan Hua , Tianbo Pan , Weiming Zhang , Dacheng Tao , Lin Wang

Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution, offering the potential to handle visual tasks in challenging scenarios. However, due to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Sheng Zhong , Zhongyang Ren , Xiya Zhu , Dehao Yuan , Cornelia Fermuller , Yi Zhou

Vision-based localization is a cost-effective and thus attractive solution for many intelligent mobile platforms. However, its accuracy and especially robustness still suffer from low illumination conditions, illumination changes, and…

Robotics · Computer Science 2024-01-17 Yi-Fan Zuo , Wanting Xu , Xia Wang , Yifu Wang , Laurent Kneip

Super-resolution (SR) is a useful technology to generate a high-resolution (HR) visual output from the low-resolution (LR) visual inputs overcoming the physical limitations of the cameras. However, SR has not been applied to enhance the…

Computer Vision and Pattern Recognition · Computer Science 2018-03-19 Hongmin Li , Guoqi Li , Hanchao Liu , Luping Shi

Event cameras are bio-inspired sensors that perform well in HDR conditions and have high temporal resolution. However, different from traditional frame-based cameras, event cameras measure asynchronous pixel-level brightness changes and…

Computer Vision and Pattern Recognition · Computer Science 2022-03-09 Xin Peng , Yifu Wang , Ling Gao , Laurent Kneip