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Event cameras output asynchronous events to represent intensity changes with a high temporal resolution, even under extreme lighting conditions. Currently, most of the existing works use a single contrast threshold to estimate the intensity…

Computer Vision and Pattern Recognition · Computer Science 2020-12-18 Ziwei Wang , Yonhon Ng , Pieter van Goor , Robert Mahony

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

Event cameras are promising devices for lowlatency tracking and high-dynamic range imaging. In this paper,we propose a novel approach for 6 degree-of-freedom (6-DoF)object motion tracking that combines measurements of eventand frame-based…

Computer Vision and Pattern Recognition · Computer Science 2022-04-11 Haolong Li , Joerg Stueckler

We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional cameras struggle with high-speed motion capture due to bandwidth and dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Ziyun Wang , Friedhelm Hamann , Kenneth Chaney , Wen Jiang , Guillermo Gallego , Kostas Daniilidis

Star trackers are primarily optical devices that are used to estimate the attitude of a spacecraft by recognising and tracking star patterns. Currently, most star trackers use conventional optical sensors. In this application paper, we…

Computer Vision and Pattern Recognition · Computer Science 2019-07-11 Tat-Jun Chin , Samya Bagchi , Anders Eriksson , Andre van Schaik

Optical flow computation with frame-based cameras provides high accuracy but the speed is limited either by the model size of the algorithm or by the frame rate of the camera. This makes it inadequate for high-speed applications. Event…

Computer Vision and Pattern Recognition · Computer Science 2022-07-25 Ashwin Sanjay Lele , Arijit Raychowdhury

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 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

In moving camera videos, motion segmentation is commonly performed using the image plane motion of pixels, or optical flow. However, objects that are at different depths from the camera can exhibit different optical flows even if they share…

Computer Vision and Pattern Recognition · Computer Science 2015-11-06 Manjunath Narayana , Allen Hanson , Erik Learned-Miller

Optical flow provides information on relative motion that is an important component in many computer vision pipelines. Neural networks provide high accuracy optical flow, yet their complexity is often prohibitive for application at the edge…

Computer Vision and Pattern Recognition · Computer Science 2023-07-13 Yannick Schnider , Stanislaw Wozniak , Mathias Gehrig , Jules Lecomte , Axel von Arnim , Luca Benini , Davide Scaramuzza , Angeliki Pantazi

Lossy compression and rate-adaptive streaming are a mainstay in traditional video steams. However, a new class of neuromorphic ``event'' sensors records video with asynchronous pixel samples rather than image frames. These sensors are…

Image and Video Processing · Electrical Eng. & Systems 2025-08-22 Andrew C. Freeman

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 such as DAVIS can simultaneously output high temporal resolution events and low frame-rate intensity images, which own great potential in capturing scene motion, such as optical flow estimation. Most of the existing optical…

Computer Vision and Pattern Recognition · Computer Science 2022-11-18 Zhexiong Wan , Yuchao Dai , Yuxin Mao

Forecasting a typical object's future motion is a critical task for interpreting and interacting with dynamic environments in computer vision. Event-based sensors, which could capture changes in the scene with exceptional temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Song Wu , Zhiyu Zhu , Junhui Hou , Guangming Shi , Jinjian Wu

We propose a robust demodulation scheme for optical camera communication systems using an event-based vision sensor, combining OOK with toggle demodulation and a digital phase-locked loop. This is the first report to achieve a $\mathrm{BER}…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Miu Sumino , Mayu Ishii , Shun Kaizu , Daisuke Hisano , Yu Nakayama

The event camera is a novel bio-inspired vision sensor. When the brightness change exceeds the preset threshold, the sensor generates events asynchronously. The number of valid events directly affects the performance of event-based tasks,…

Computer Vision and Pattern Recognition · Computer Science 2022-08-24 Xijie Xiang , Lin Zhu , Jianing Li , Yonghong Tian , Tiejun Huang

We present a unifying framework to solve several computer vision problems with event cameras: motion, depth and optical flow estimation. The main idea of our framework is to find the point trajectories on the image plane that are best…

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

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

Aerial surveillance demands rapid and precise detection of moving objects in dynamic environments. Event cameras, which draw inspiration from biological vision systems, present a promising alternative to frame-based sensors due to their…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Sami Arja , Alexandre Marcireau , Saeed Afshar , Bharath Ramesh , Gregory Cohen

Event-cameras have emerged as a revolutionary technology with a high temporal resolution that far surpasses standard active pixel cameras. This technology draws biological inspiration from photoreceptors and the initial retinal synapse.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Victoria Clerico , Shay Snyder , Arya Lohia , Md Abdullah-Al Kaiser , Gregory Schwartz , Akhilesh Jaiswal , Maryam Parsa