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Camera calibration is an important prerequisite towards the solution of 3D computer vision problems. Traditional methods rely on static images of a calibration pattern. This raises interesting challenges towards the practical usage of event…

Computer Vision and Pattern Recognition · Computer Science 2021-07-29 Kun Huang , Yifu Wang , Laurent Kneip

Neuromorphic cameras, also known as event-based cameras, can detect changes in the environmental brightness asynchronously and independently for each pixel. They output the brightness changes, i.e., events, as 3-D (2-D pixel coordinates +…

Image and Video Processing · Electrical Eng. & Systems 2026-05-21 Shimpei Harada , Junya Hara , Hiroshi Higashi , Yuichi Tanaka

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 2018-04-06 Antoni Rosinol Vidal , Henri Rebecq , Timo Horstschaefer , Davide Scaramuzza

Many applications of stereo depth estimation in robotics require the generation of accurate disparity maps in real time under significant computational constraints. Current state-of-the-art algorithms force a choice between either…

Computer Vision and Pattern Recognition · Computer Science 2019-03-06 Yan Wang , Zihang Lai , Gao Huang , Brian H. Wang , Laurens van der Maaten , Mark Campbell , Kilian Q. Weinberger

Event sensors output a stream of asynchronous brightness changes (called ``events'') at a very high temporal rate. Previous works on recovering the lost intensity information from the event sensor data have heavily relied on the event…

Computer Vision and Pattern Recognition · Computer Science 2020-03-18 Prasan A Shedligeri , Kaushik Mitra

Event cameras are sensors inspired by biological systems that specialize in capturing changes in brightness. These emerging cameras offer many advantages over conventional frame-based cameras, including high dynamic range, high frame rates,…

Computer Vision and Pattern Recognition · Computer Science 2023-09-04 Haodong Chen , Vera Chung , Li Tan , Xiaoming Chen

The stereo event-intensity camera setup is widely applied to leverage the advantages of both event cameras with low latency and intensity cameras that capture accurate brightness and texture information. However, such a setup commonly…

Computer Vision and Pattern Recognition · Computer Science 2023-07-18 Chao Ding , Mingyuan Lin , Haijian Zhang , Jianzhuang Liu , Lei Yu

Event cameras are emerging imaging technology that offers advantages over conventional frame-based imaging sensors in dynamic range and sensing speed. Complementing the rich texture and color perception of traditional image frames, the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Peiqi Duan , Boyu Li , Yixin Yang , Hanyue Lou , Minggui Teng , Yi Ma , Boxin Shi

Event cameras are bio-inspired vision sensors that asynchronously measure per-pixel brightness changes.The high-temporal resolution and asynchronicity of event cameras offer great potential for estimating robot motion states. Recent works…

Robotics · Computer Science 2025-01-07 Zhixiang Wang , Xudong Li , Yizhai Zhang , Panfeng Huang

As neuromorphic sensors, event cameras asynchronously record changes in brightness as streams of sparse events with the advantages of high temporal resolution and high dynamic range. Reconstructing intensity images from events is a highly…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Weilun Li , Lei Sun , Ruixi Gao , Qi Jiang , Yuqin Ma , Kaiwei Wang , Ming-Hsuan Yang , Luc Van Gool , Danda Pani Paudel

As the ubiquity of smart mobile devices continues to rise, Optical Camera Communication systems have gained more attention as a solution for efficient and private data streaming. This system utilizes optical cameras to receive data from…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Hang Su , Ling Gao , Tao Liu , Laurent Kneip

Dynamic Vision Sensor (DVS) event camera models are important tools for predicting camera response, optimizing biases, and generating realistic simulated datasets. Existing DVS models have been useful, but have not demonstrated high realism…

Image and Video Processing · Electrical Eng. & Systems 2025-05-13 Rui Graca , Tobi Delbruck

Low-light image enhancement aims to restore the under-exposure image captured in dark scenarios. Under such scenarios, traditional frame-based cameras may fail to capture the structure and color information due to the exposure time…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Xuejian Guo , Zhiqiang Tian , Yuehang Wang , Siqi Li , Yu Jiang , Shaoyi Du , Yue Gao

Understanding human movement and city dynamics has always been challenging. From traditional methods of manually observing the city's inhabitant, to using cameras, to now using sensors and more complex technology, the field of urban…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Jack Brady , Andrew Dailey , Kristen Schang , Zo Vic Shong

This study introduces a novel approach to enhance the spatial-temporal resolution of time-event pixels based on luminance changes captured by event cameras. These cameras present unique challenges due to their low resolution and the sparse,…

Image and Video Processing · Electrical Eng. & Systems 2024-08-14 Waseem Shariff , Joe Lemley , Peter Corcoran

Active depth sensors like structured light, lidar, and time-of-flight systems sample the depth of the entire scene uniformly at a fixed scan rate. This leads to limited spatio-temporal resolution where redundant static information is…

Computer Vision and Pattern Recognition · Computer Science 2021-12-21 Manasi Muglikar , Diederik Paul Moeys , Davide Scaramuzza

Event cameras are novel, bio-inspired visual sensors, whose pixels output asynchronous and independent timestamped spikes at local intensity changes, called 'events'. Event cameras offer advantages over conventional frame-based cameras in…

Computer Vision and Pattern Recognition · Computer Science 2019-04-25 Cedric Scheerlinck , Henri Rebecq , Timo Stoffregen , Nick Barnes , Robert Mahony , Davide Scaramuzza

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-based cameras are popular for tracking fast-moving objects due to their high temporal resolution, low latency, and high dynamic range. In this paper, we propose a novel algorithm for tracking event blobs using raw events…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Ziwei Wang , Timothy Molloy , Pieter van Goor , Robert Mahony

Conventional frame-based cameras often struggle with stereo depth estimation in rapidly changing scenes. In contrast, bio-inspired spike cameras emit asynchronous events at microsecond-level resolution, providing an alternative sensing…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Zhuoheng Gao , Yihao Li , Jiyao Zhang , Rui Zhao , Tong Wu , Hao Tang , Zhaofei Yu , Hao Dong , Guozhang Chen , Tiejun Huang