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New vision sensors, such as the Dynamic and Active-pixel Vision sensor (DAVIS), incorporate a conventional global-shutter camera and an event-based sensor in the same pixel array. These sensors have great potential for high-speed robotics…

Robotics · Computer Science 2017-11-10 Elias Mueggler , Henri Rebecq , Guillermo Gallego , Tobi Delbruck , Davide Scaramuzza

Event cameras have a lot of advantages over traditional cameras, such as low latency, high temporal resolution, and high dynamic range. However, since the outputs of event cameras are the sequences of asynchronous events overtime rather…

Computer Vision and Pattern Recognition · Computer Science 2020-10-13 S. Mohammad Mostafavi I. , Lin Wang , Yo-Sung Ho , Kuk-Jin Yoon

Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events". They have appealing advantages over frame-based cameras for computer vision, including high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Daniel Gehrig , Antonio Loquercio , Konstantinos G. Derpanis , Davide Scaramuzza

Event cameras are bio-inspired sensors that offer advantages over traditional cameras. They operate asynchronously, sampling the scene at microsecond resolution and producing a stream of brightness changes. This unconventional output has…

Computer Vision and Pattern Recognition · Computer Science 2022-09-14 Suman Ghosh , Guillermo Gallego

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 camera-based pattern recognition is a newly arising research topic in recent years. Current researchers usually transform the event streams into images, graphs, or voxels, and adopt deep neural networks for event-based classification.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Xiao Wang , Yao Rong , Zongzhen Wu , Lin Zhu , Bo Jiang , Jin Tang , Yonghong Tian

Recording fast motion in a high FPS (frame-per-second) requires expensive high-speed cameras. As an alternative, interpolating low-FPS videos from commodity cameras has attracted significant attention. If only low-FPS videos are available,…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Weihua He , Kaichao You , Zhendong Qiao , Xu Jia , Ziyang Zhang , Wenhui Wang , Huchuan Lu , Yaoyuan Wang , Jianxing Liao

We present a system for 3D semantic scene perception consisting of a network of distributed smart edge sensors. The sensor nodes are based on an embedded CNN inference accelerator and RGB-D and thermal cameras. Efficient vision CNN models…

Computer Vision and Pattern Recognition · Computer Science 2022-05-04 Simon Bultmann , Sven Behnke

Event cameras are advantageous for tasks that require vision sensors with low-latency and sparse output responses. However, the development of deep network algorithms using event cameras has been slow because of the lack of large labelled…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Joachim Ott , Zuowen Wang , Shih-Chii Liu

Event cameras are novel vision sensors that sample, in an asynchronous fashion, brightness increments with low latency and high temporal resolution. The resulting streams of events are of high value by themselves, especially for high speed…

Computer Vision and Pattern Recognition · Computer Science 2021-04-13 F. Paredes-Vallés , G. C. H. E. de Croon

Event-based sensors offer high temporal resolution and low latency by generating sparse, asynchronous data. However, converting this irregular data into dense tensors for use in standard neural networks diminishes these inherent advantages,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Aayush Atul Verma , Arpitsinh Vaghela , Bharatesh Chakravarthi , Kaustav Chanda , Yezhou Yang

Simulating event streams from 3D scenes has become a common practice in event-based vision research, as it meets the demand for large-scale, high temporal frequency data without setting up expensive hardware devices or undertaking extensive…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zhenyang Li , Xiaoyang Bai , Jinfan Lu , Pengfei Shen , Edmund Y. Lam , Yifan Peng

Recognizing and comprehending human actions and gestures is a crucial perception requirement for robots to interact with humans and carry out tasks in diverse domains, including service robotics, healthcare, and manufacturing. Event…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Tristan de Blegiers , Ishan Rajendrakumar Dave , Adeel Yousaf , Mubarak Shah

Event cameras capture asynchronous pixel-level brightness changes with microsecond temporal resolution, offering unique advantages for high-speed vision tasks. Existing methods often convert event streams into intermediate representations…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Hanfang Liang , Bing Wang , Shizhen Zhang , Wen Jiang , Yizhuo Yang , Weixiang Guo , Shenghai Yuan

Active vision enables dynamic visual perception, offering an alternative to static feedforward architectures in computer vision, which rely on large datasets and high computational resources. Biological selective attention mechanisms allow…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Giulia D'Angelo , Victoria Clerico , Chiara Bartolozzi , Matej Hoffmann , P. Michael Furlong , Alexander Hadjiivanov

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

Human pose estimation focuses on predicting body keypoints to analyze human motion. Currently, most pose estimation tasks rely on conventional RGB cameras. In contrast, event cameras provide high temporal resolution and low latency,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Haoxian Zhou , Chuanzhi Xu , Langyi Chen , Pengfei Ye , Haodong Chen , Yuk Ying Chung , Qiang Qu

Road segmentation is pivotal for autonomous vehicles, yet achieving low latency and low compute solutions using frame based cameras remains a challenge. Event cameras offer a promising alternative. To leverage their low power sensing, we…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Lakshmi Annamalai , Chetan Singh Thakur

Event cameras are a new type of vision sensor that incorporates asynchronous and independent pixels, offering advantages over traditional frame-based cameras such as high dynamic range and minimal motion blur. However, their output is not…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Burak Ercan , Onur Eker , Aykut Erdem , Erkut Erdem

An event-based state estimation approach for reducing communication in a networked control system is proposed. Multiple distributed sensor agents observe a dynamic process and sporadically transmit their measurements to estimator agents…

Systems and Control · Computer Science 2017-03-27 Sebastian Trimpe
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