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The current event cameras are bio-inspired sensors that respond to brightness changes in the scene asynchronously and independently for every pixel, and transmit these changes as ternary event streams. Event cameras have several benefits…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Eero Lehtonen , Tuomo Komulainen , Ari Paasio , Mika Laiho

Line segment extraction is effective for capturing geometric features of human-made environments. Event-based cameras, which asynchronously respond to contrast changes along edges, enable efficient extraction by reducing redundant data.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Mikihiro Ikura , Arren Glover , Masayoshi Mizuno , Chiara Bartolozzi

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-based cameras (ECs) are bio-inspired sensors that asynchronously report brightness changes for each pixel. Due to their high dynamic range, pixel bandwidth, temporal resolution, low power consumption, and computational simplicity,…

Robotics · Computer Science 2022-07-26 Seyed Ehsan Marjani Bajestani , Giovanni Beltrame

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

Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low-frequency reference intensity information. These…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Cedric Scheerlinck , Nick Barnes , Robert Mahony

Event cameras are bio-inspired vision sensors that mimic retinas to asynchronously report per-pixel intensity changes rather than outputting an actual intensity image at regular intervals. This new paradigm of image sensor offers…

Computer Vision and Pattern Recognition · Computer Science 2019-04-02 Yusuke Sekikawa , Kosuke Hara , Hideo Saito

Event-based vision sensors, such as the Dynamic Vision Sensor (DVS), are ideally suited for real-time motion analysis. The unique properties encompassed in the readings of such sensors provide high temporal resolution, superior sensitivity…

Computer Vision and Pattern Recognition · Computer Science 2020-01-14 Anton Mitrokhin , Cornelia Fermuller , Chethan Parameshwara , Yiannis Aloimonos

Detecting and magnifying imperceptible high-frequency motions in real-world scenarios has substantial implications for industrial and medical applications. These motions are characterized by small amplitudes and high frequencies.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Yutian Chen , Shi Guo , Fangzheng Yu , Feng Zhang , Jinwei Gu , Tianfan Xue

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

Event cameras are rapidly emerging as powerful vision sensors for 3D reconstruction, uniquely capable of asynchronously capturing per-pixel brightness changes. Compared to traditional frame-based cameras, event cameras produce sparse yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Chuanzhi Xu , Haoxian Zhou , Langyi Chen , Haodong Chen , Zeke Zexi Hu , Zhicheng Lu , Ying Zhou , Vera Chung , Qiang Qu , Weidong Cai

Dynamic vision sensors or event cameras provide rich complementary information for video frame interpolation. Existing state-of-the-art methods follow the paradigm of combining both synthesis-based and warping networks. However, few of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Jiaben Chen , Yichen Zhu , Dongze Lian , Jiaqi Yang , Yifu Wang , Renrui Zhang , Xinhang Liu , Shenhan Qian , Laurent Kneip , Shenghua Gao

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

Identifying independently moving objects is an essential task for dynamic scene understanding. However, traditional cameras used in dynamic scenes may suffer from motion blur or exposure artifacts due to their sampling principle. By…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Yi Zhou , Guillermo Gallego , Xiuyuan Lu , Siqi Liu , Shaojie Shen

Event-based camera is a bio-inspired vision sensor that records intensity changes (called event) asynchronously in each pixel. As an instance of event-based camera, Dynamic and Active-pixel Vision Sensor (DAVIS) combines a standard camera…

Computer Vision and Pattern Recognition · Computer Science 2019-04-29 Yuhu Guo , Han Xiao , Yidong Chen , Xiaodong Shi

Imitation from videos often fails when expert demonstrations and learner environments exhibit domain shifts, such as discrepancies in lighting, color, or texture. While visual randomization partially addresses this problem by augmenting…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Andrea Ramazzina , Vittorio Giammarino , Matteo El-Hariry , Mario Bijelic

Event-based vision, characterized by low redundancy, focus on dynamic motion, and inherent privacy-preserving properties, naturally fits the demands of video anomaly detection (VAD). However, the absence of dedicated event-stream anomaly…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Peng Wu , Yuting Yan , Guansong Pang , Yujia Sun , Qingsen Yan , Peng Wang , Yanning Zhang

The cameras in modern gaze-tracking systems suffer from fundamental bandwidth and power limitations, constraining data acquisition speed to 300 Hz realistically. This obstructs the use of mobile eye trackers to perform, e.g., low latency…

Computer Vision and Pattern Recognition · Computer Science 2022-08-09 Anastasios N. Angelopoulos , Julien N. P. Martel , Amit P. S. Kohli , Jorg Conradt , Gordon Wetzstein

Event-based cameras are dynamic vision sensors that provide asynchronous measurements of changes in per-pixel brightness at a microsecond level. This makes them significantly faster than conventional frame-based cameras, and an appealing…

Computer Vision and Pattern Recognition · Computer Science 2021-10-01 Sai Vemprala , Sami Mian , Ashish Kapoor

3D hand pose estimation from monocular videos is a long-standing and challenging problem, which is now seeing a strong upturn. In this work, we address it for the first time using a single event camera, i.e., an asynchronous vision sensor…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Viktor Rudnev , Vladislav Golyanik , Jiayi Wang , Hans-Peter Seidel , Franziska Mueller , Mohamed Elgharib , Christian Theobalt