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Event cameras asynchronously capture brightness changes with low latency, high temporal resolution, and high dynamic range. However, annotation of event data is a costly and laborious process, which limits the use of deep learning methods…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Simon Klenk , David Bonello , Lukas Koestler , Nikita Araslanov , Daniel Cremers

Event cameras are neuromorphic sensors that capture asynchronous and sparse event stream when per-pixel brightness changes. The state-of-the-art processing methods for event signals typically aggregate events into a frame or a grid.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Beibei Yang , Weiling Li , Yan Fang

The development of aerial autonomy has enabled aerial robots to fly agilely in complex environments. However, dodging fast-moving objects in flight remains a challenge, limiting the further application of unmanned aerial vehicles (UAVs).…

Robotics · Computer Science 2021-03-12 Botao He , Haojia Li , Siyuan Wu , Dong Wang , Zhiwei Zhang , Qianli Dong , Chao Xu , Fei Gao

With the increasing complexity of mobile device applications, these devices are evolving toward high agility. This shift imposes new demands on mobile sensing, particularly in achieving high-accuracy and low-latency. Event-based vision has…

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

Event-based vision represents a paradigm shift in how vision information is captured and processed. By only responding to dynamic intensity changes in the scene, event-based sensing produces far less data than conventional frame-based…

Hardware Architecture · Computer Science 2024-04-09 Yizhao Gao , Baoheng Zhang , Yuhao Ding , Hayden Kwok-Hay So

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

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

Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". Due to their sensing mechanism, event cameras have little to no motion blur, a very high temporal resolution…

Computer Vision and Pattern Recognition · Computer Science 2022-04-05 Chiara Plizzari , Mirco Planamente , Gabriele Goletto , Marco Cannici , Emanuele Gusso , Matteo Matteucci , Barbara Caputo

Event-based cameras offer much potential to the fields of robotics and computer vision, in part due to their large dynamic range and extremely high "frame rates". These attributes make them, at least in theory, particularly suitable for…

Event cameras offer low-power visual sensing capabilities ideal for edge-device applications. However, their high event rate, driven by high temporal details, can be restrictive in terms of bandwidth and computational resources. In edge AI…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Hesam Araghi , Jan van Gemert , Nergis Tomen

Event-based cameras have recently drawn the attention of the Computer Vision community thanks to their advantages in terms of high temporal resolution, low power consumption and high dynamic range, compared to traditional frame-based…

Computer Vision and Pattern Recognition · Computer Science 2018-03-22 Amos Sironi , Manuele Brambilla , Nicolas Bourdis , Xavier Lagorce , Ryad Benosman

The event camera's low power consumption and ability to capture microsecond brightness changes make it attractive for various computer vision tasks. Existing event representation methods typically convert events into frames, voxel grids, or…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Bin Jiang , Zhihao Li , M. Salman Asif , Xun Cao , Zhan Ma

Focus control (FC) is crucial for cameras to capture sharp images in challenging real-world scenarios. The autofocus (AF) facilitates the FC by automatically adjusting the focus settings. However, due to the lack of effective AF methods for…

Computer Vision and Pattern Recognition · Computer Science 2022-03-24 Shijie Lin , Yinqiang Zhang , Lei Yu , Bin Zhou , Xiaowei Luo , Jia Pan

Event cameras detect changes in per-pixel intensity to generate asynchronous `event streams'. They offer great potential for accurate semantic map retrieval in real-time autonomous systems owing to their much higher temporal resolution and…

Computer Vision and Pattern Recognition · Computer Science 2023-09-29 Shristi Das Biswas , Adarsh Kosta , Chamika Liyanagedera , Marco Apolinario , Kaushik Roy

Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). However, the detection of obstacles especially during night-time is still a challenging task since the lighting conditions are…

Computer Vision and Pattern Recognition · Computer Science 2020-12-17 Jawad N. Yasin , Sherif A. S. Mohamed , Mohammad-hashem Haghbayan , Jukka Heikkonen , Hannu Tenhunen , Muhammad Mehboob Yasin , Juha Plosila

Event cameras are innovative neuromorphic sensors that asynchronously capture the scene dynamics. Due to the event-triggering mechanism, such cameras record event streams with much shorter response latency and higher intensity sensitivity…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Yunhao Zou , Ying Fu , Tsuyoshi Takatani , Yinqiang Zheng

Event cameras asynchronously output low-latency event streams, promising for state estimation in high-speed motion and challenging lighting conditions. As opposed to frame-based cameras, the motion-dependent nature of event cameras presents…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Peiyu Chen , Fuling Lin , Weipeng Guan , Peng Lu

Event cameras are neuromorphic vision sensors that record a scene as sparse and asynchronous event streams. Most event-based methods project events into dense frames and process them using conventional vision models, resulting in high…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Bochen Xie , Yongjian Deng , Zhanpeng Shao , Qingsong Xu , Youfu Li

Event vision sensors (neuromorphic cameras) output sparse, asynchronous ON/OFF events triggered by log-intensity threshold crossings, enabling microsecond-scale sensing with high dynamic range and low data bandwidth. As a nonlinear system,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Nimrod Kruger , Nicholas Owen Ralph , Gregory Cohen , Paul Hurley
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