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Event Cameras, also known as Neuromorphic sensors, capture changes in local light intensity at the pixel level, producing asynchronously generated data termed ``events''. This distinct data format mitigates common issues observed in…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Khadija Iddrisu , Waseem Shariff , Noel E. OConnor , Joseph Lemley , Suzanne Little

Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events". They have appealing advantages over frame-based cameras for computer vision, including high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Daniel Gehrig , Antonio Loquercio , Konstantinos G. Derpanis , Davide Scaramuzza

Event cameras are bioinspired sensors with reaction times in the order of microseconds. This property makes them appealing for use in highly-dynamic computer vision applications. In this work,we explore the limits of this sensing technology…

Computer Vision and Pattern Recognition · Computer Science 2020-10-14 William Chamorro , Juan Andrade-Cetto , Joan Solà

Event cameras are a kind of bio-inspired sensors that generate data when the brightness changes, which are of low-latency and high dynamic range (HDR). However, due to the nature of the sparse event stream, event-based mapping can only…

Robotics · Computer Science 2021-06-04 Yan Dong

Event cameras, inspired by biological vision, are asynchronous sensors that detect changes in brightness, offering notable advantages in environments characterized by high-speed motion, low lighting, or wide dynamic range. These distinctive…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Jiaqiang Zhang , Xianjia Yu , Ha Sier , Haizhou Zhang , Tomi Westerlund

This paper presents a novel approach of representing dynamic visual scenes with static maps generated from video/image streams. Such representation allows easy visual assessment of motion in dynamic environments. These maps are 2D matrices…

Computer Vision and Pattern Recognition · Computer Science 2021-03-05 Bruno Costa , Enrique Corona , Mostafa Parchami , Gint Puskorius , Dimitar Filev

Event-based sensors detect only changes in brightness across a scene, with each pixel producing an asynchronous stream of spatial-temporal data, rather than recording frames of overall illumination such as a traditional frame-based sensor.…

Instrumentation and Methods for Astrophysics · Physics 2025-04-10 Monique Cockram , Noelia Martinez Rey

A long-standing challenge in scene analysis is the recovery of scene arrangements under moderate to heavy occlusion, directly from monocular video. While the problem remains a subject of active research, concurrent advances have been made…

Graphics · Computer Science 2019-07-19 Aron Monszpart , Paul Guerrero , Duygu Ceylan , Ersin Yumer , Niloy J. Mitra

Neuromorphic imaging reacts to per-pixel brightness changes of a dynamic scene with high temporal precision and responds with asynchronous streaming events as a result. It also often supports a simultaneous output of an intensity image.…

Image and Video Processing · Electrical Eng. & Systems 2024-03-25 Pei Zhang , Haosen Liu , Zhou Ge , Chutian Wang , Edmund Y. Lam

Single-shot ultrafast optical imaging plays a very important role in the detection of transient scenes, especially in capturing irreversible or stochastic dynamic scenes. To break the limit of time response speed of electronic devices, such…

When sound waves hit an object, they induce vibrations that produce high-frequency and subtle visual changes, which can be used for recovering the sound. Early studies always encounter trade-offs related to sampling rate, bandwidth, field…

Sound · Computer Science 2025-04-04 Hao Yin , Shi Guo , Xu Jia , Xudong XU , Lu Zhang , Si Liu , Dong Wang , Huchuan Lu , Tianfan Xue

Fast neuromorphic event-based vision sensors (Dynamic Vision Sensor, DVS) can be combined with slower conventional frame-based sensors to enable higher-quality inter-frame interpolation than traditional methods relying on fixed motion…

Computer Vision and Pattern Recognition · Computer Science 2021-12-20 Adam Radomski , Andreas Georgiou , Thomas Debrunner , Chenghan Li , Luca Longinotti , Minwon Seo , Moosung Kwak , Chang-Woo Shin , Paul K. J. Park , Hyunsurk Eric Ryu , Kynan Eng

Event-based cameras are neuromorphic sensors capable of efficiently encoding visual information in the form of sparse sequences of events. Being biologically inspired, they are commonly used to exploit some of the computational and power…

Computer Vision and Pattern Recognition · Computer Science 2018-11-20 Marco Cannici , Marco Ciccone , Andrea Romanoni , Matteo Matteucci

Advances in vectorial polarisation-resolved imaging are bringing new capabilities to applications ranging from fundamental physics through to clinical diagnosis. Imaging polarimetry requires determination of the Mueller matrix (MM) at every…

High dynamic range (HDR) imaging is a crucial task in computational photography, which captures details across diverse lighting conditions. Traditional HDR fusion methods face limitations in dynamic scenes with extreme exposure differences,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Shi Guo , Zixuan Chen , Ziran Zhang , Yutian Chen , Gangwei Xu , Tianfan Xue

Recently, we have witnessed the rise of novel ``event-based'' camera sensors for high-speed, low-power video capture. Rather than recording discrete image frames, these sensors output asynchronous ``event'' tuples with microsecond…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Andrew Hamara , Benjamin Kilpatrick , Alex Baratta , Brendon Kofink , Andrew C. Freeman

Accurately capturing dynamic scenes with wide-ranging motion and light intensity is crucial for many vision applications. However, acquiring high-speed high dynamic range (HDR) video is challenging because the camera's frame rate restricts…

Image and Video Processing · Electrical Eng. & Systems 2024-04-26 Caixin Wang , Jie Zhang , Matthew A. Wilson , Ralph Etienne-Cummings

Event camera is an emerging imaging sensor for capturing dynamics of moving objects as events, which motivates our work in estimating 3D human pose and shape from the event signals. Events, on the other hand, have their unique challenges:…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Shihao Zou , Chuan Guo , Xinxin Zuo , Sen Wang , Pengyu Wang , Xiaoqin Hu , Shoushun Chen , Minglun Gong , Li Cheng

Event stereo matching is an emerging technique to estimate depth from neuromorphic cameras; however, events are unlikely to trigger in the absence of motion or the presence of large, untextured regions, making the correspondence problem…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Luca Bartolomei , Matteo Poggi , Andrea Conti , Stefano Mattoccia

Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes in microsecond accuracy with a high dynamic range and low power consumption. Despite these advantages, event cameras cannot be directly applied to…

Computer Vision and Pattern Recognition · Computer Science 2022-11-02 Jinjin Gu , Jinan Zhou , Ringo Sai Wo Chu , Yan Chen , Jiawei Zhang , Xuanye Cheng , Song Zhang , Jimmy S. Ren
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