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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,…

Visual Deformation Measurement (VDM) aims to recover dense deformation fields by tracking surface motion from camera observations. Traditional image-based methods rely on minimal inter-frame motion to constrain the correspondence search…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Yuliang Wu , Wei Zhai , Yuxin Cui , Tiesong Zhao , Yang Cao , Zheng-Jun Zha

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Guillermo Gallego , Jon E. A. Lund , Elias Mueggler , Henri Rebecq , Tobi Delbruck , Davide Scaramuzza

In Intelligent Transportation Systems (ITS), multi-object tracking is primarily based on frame-based cameras. However, these cameras tend to perform poorly under dim lighting and high-speed motion conditions. Event cameras, characterized by…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Mengyu Li , Xingcheng Zhou , Guang Chen , Alois Knoll , Hu Cao

Event-based imaging is a neurmorphic detection technique whereby an array of pixels detects a positive or negative change in light intensity at each pixel, and is hence particularly well suited to detecting motion. As compared to standard…

Instrumentation and Detectors · Physics 2022-09-16 Yugang Ren , Enrique Benedetto , Harry Borrill , Yelizaveta Savchuk , Molly Message , Katie O'Flynn , Muddassar Rashid , James Millen

In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called "events"), with microsecond…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Timo Stoffregen , Guillermo Gallego , Tom Drummond , Lindsay Kleeman , Davide Scaramuzza

Inspired by the complementarity between conventional frame-based and bio-inspired event-based cameras, we propose a multi-modal based approach to fuse visual cues from the frame- and event-domain to enhance the single object tracking…

Computer Vision and Pattern Recognition · Computer Science 2021-09-21 Jiqing Zhang , Xin Yang , Yingkai Fu , Xiaopeng Wei , Baocai Yin , Bo Dong

Gait recognition enables non-intrusive, privacy-preserving identification but suffers in uncontrolled environments due to illumination and motion sensitivity of conventional cameras. In this work, we explore gait recognition using event…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Senyan Xu , Shuai Chen , Chuanfu Shen , Kean Liu , Zhijing Sun , Chengzhi Cao , Xueyang Fu

Event cameras are a paradigm shift in camera technology. Instead of full frames, the sensor captures a sparse set of events caused by intensity changes. Since only the changes are transferred, those cameras are able to capture quick…

Computer Vision and Pattern Recognition · Computer Science 2017-03-22 Christian Reinbacher , Gottfried Munda , Thomas Pock

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 high-speed maneuvering scenarios.…

Event cameras are an interesting visual exteroceptive sensor that reacts to brightness changes rather than integrating absolute image intensities. Owing to this design, the sensor exhibits strong performance in situations of challenging…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Runze Yuan , Tao Liu , Zijia Dai , Yi-Fan Zuo , Laurent Kneip

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

With the increasing complexity of mobile device applications, these devices are evolving toward high agility. This shift imposes new demands on mobile sensing, particularly in achieving high-accuracy and low-latency. Event-based vision has…

Object detection plays a critical role in autonomous driving, where accurately and efficiently detecting objects in fast-moving scenes is crucial. Traditional frame-based cameras face challenges in balancing latency and bandwidth,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Bingquan Zhou , Jie Jiang

Among prerequisites for a synthetic agent to interact with dynamic scenes, the ability to identify independently moving objects is specifically important. From an application perspective, nevertheless, standard cameras may deteriorate…

Computer Vision and Pattern Recognition · Computer Science 2021-11-08 Xiuyuan Lu , Yi Zhou , Shaojie Shen

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

Event-based cameras are bio-inspired vision sensors whose pixels work independently from each other and respond asynchronously to brightness changes, with microsecond resolution. Their advantages make it possible to tackle challenging…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Yi Zhou , Guillermo Gallego , Shaojie Shen

This work addresses the issue of motion compensation and pattern tracking in event camera data. An event camera generates asynchronous streams of events triggered independently by each of the pixels upon changes in the observed intensity.…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Cedric Le Gentil , Ignacio Alzugaray , Teresa Vidal-Calleja

Predicting a potential collision with leading vehicles is an essential functionality of any autonomous/assisted driving system. One bottleneck of existing vision-based solutions is that their updating rate is limited to the frame rate of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Jinghang Li , Bangyan Liao , Xiuyuan LU , Peidong Liu , Shaojie Shen , Yi Zhou

We focus on a very challenging task: imaging at nighttime dynamic scenes. Most previous methods rely on the low-light enhancement of a conventional RGB camera. However, they would inevitably face a dilemma between the long exposure time of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Haoyue Liu , Shihan Peng , Lin Zhu , Yi Chang , Hanyu Zhou , Luxin Yan