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Related papers: EE3P: Event-based Estimation of Periodic Phenomena…

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We present a novel method for measuring the rate of periodic phenomena (e.g., rotation, flicker, and vibration), by an event camera, a device asynchronously reporting brightness changes at independently operating pixels with high temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Jakub Kolář , Radim Špetlík , Jiří Matas

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

Being inspired by the biological eye, event camera is a novel asynchronous technology that pose a paradigm shift in acquisition of visual information. This paradigm enables event cameras to capture pixel-size fast motions much more…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 David El-Chai Ben-Ezra , Ron Arad , Ayelet Padowicz , Israel Tugendhaft

Event-based vision sensors mimic the operation of biological retina and they represent a major paradigm shift from traditional cameras. Instead of providing frames of intensity measurements synchronously, at artificially chosen rates,…

Computer Vision and Pattern Recognition · Computer Science 2015-10-08 Guillermo Gallego , Christian Forster , Elias Mueggler , Davide Scaramuzza

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,…

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 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 camera is a new type of sensor that is different from traditional cameras. Each pixel is triggered asynchronously by an event. The trigger event is the change of the brightness irradiated on the pixel. If the increment or decrement is…

Computer Vision and Pattern Recognition · Computer Science 2022-03-28 Kun Xiao , Pengju Li , Guohui Wang , Zhi Li , Yi Chen , Yongfeng Xie , Yuqiang Fang

Event cameras are novel bio-inspired sensors that offer advantages over traditional cameras (low latency, high dynamic range, low power, etc.). Optical flow estimation methods that work on packets of events trade off speed for accuracy,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Shintaro Shiba , Yoshimitsu Aoki , Guillermo Gallego

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

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

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

3D object detection is essential for autonomous systems, enabling precise localization and dimension estimation. While LiDAR and RGB cameras are widely used, their fixed frame rates create perception gaps in high-speed scenarios. Event…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Jae-Young Kang , Hoonhee Cho , Kuk-Jin Yoon

State-of-the-art solutions for Shape-from-Polarization (SfP) suffer from a speed-resolution tradeoff: they either sacrifice the number of polarization angles measured or necessitate lengthy acquisition times due to framerate constraints,…

Computer Vision and Pattern Recognition · Computer Science 2023-04-12 Manasi Muglikar , Leonard Bauersfeld , Diederik Paul Moeys , Davide Scaramuzza

Event-based cameras are biologically inspired sensors that output asynchronous pixel-wise brightness changes in the scene called events. They have a high dynamic range and temporal resolution of a microsecond, opposed to standard cameras…

Robotics · Computer Science 2019-07-18 Antea Hadviger , Ivan Marković , Ivan Petrović

This paper proposes a novel method for human hands tracking using data from an event camera. The event camera detects changes in brightness, measuring motion, with low latency, no motion blur, low power consumption and high dynamic range.…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Laura Duarte , Mohammad Safeea , Pedro Neto

State-of-the-art frame interpolation methods generate intermediate frames by inferring object motions in the image from consecutive key-frames. In the absence of additional information, first-order approximations, i.e. optical flow, must be…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Stepan Tulyakov , Daniel Gehrig , Stamatios Georgoulis , Julius Erbach , Mathias Gehrig , Yuanyou Li , Davide Scaramuzza

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

This paper presents a new method for 3D depth estimation using the output of an asynchronous time driven image sensor. In association with a high speed Digital Light Processing projection system, our method achieves real-time reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 T. Leroux , S. -H. Ieng , R. Benosman

Event cameras offer unparalleled advantages for real-time perception in dynamic environments, thanks to the microsecond-level temporal resolution and asynchronous operation. Existing event detectors, however, are limited by fixed-frequency…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Dongyue Lu , Lingdong Kong , Gim Hee Lee , Camille Simon Chane , Wei Tsang Ooi
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