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Identifying independently moving objects is an essential task for dynamic scene understanding. However, traditional cameras used in dynamic scenes may suffer from motion blur or exposure artifacts due to their sampling principle. By…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Yi Zhou , Guillermo Gallego , Xiuyuan Lu , Siqi Liu , Shaojie Shen

Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution, offering the potential to handle visual tasks in challenging scenarios. However, due to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Sheng Zhong , Zhongyang Ren , Xiya Zhu , Dehao Yuan , Cornelia Fermuller , Yi Zhou

Rapid and reliable identification of dynamic scene parts, also known as motion segmentation, is a key challenge for mobile sensors. Contemporary RGB camera-based methods rely on modeling camera and scene properties however, are often…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Stamatios Georgoulis , Weining Ren , Alfredo Bochicchio , Daniel Eckert , Yuanyou Li , Abel Gawel

Event cameras provide rich signals that are suitable for motion estimation since they respond to changes in the scene. As any visual changes in the scene produce event data, it is paramount to classify the data into different motions (i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Ryo Yamaki , Shintaro Shiba , Guillermo Gallego , Yoshimitsu Aoki

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 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

Among prerequisites for a synthetic agent to interact with dynamic scenes, the ability to identify independently moving objects is specifically important. From an application perspective, nevertheless, standard cameras may deteriorate…

Computer Vision and Pattern Recognition · Computer Science 2021-11-08 Xiuyuan Lu , Yi Zhou , Shaojie Shen

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 encode visual information with high temporal precision, low data-rate, and high-dynamic range. Thanks to these characteristics, event cameras are particularly suited for scenarios with high motion, challenging lighting…

Computer Vision and Pattern Recognition · Computer Science 2020-12-10 Etienne Perot , Pierre de Tournemire , Davide Nitti , Jonathan Masci , Amos Sironi

Event cameras are novel bio-inspired sensors that capture motion dynamics with much higher temporal resolution than traditional cameras, since pixels react asynchronously to brightness changes. They are therefore better suited for tasks…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Youssef Farah , Federico Paredes-Vallés , Guido De Croon , Muhammad Ahmed Humais , Hussain Sajwani , Yahya Zweiri

Segmentation of moving objects in dynamic scenes is a key process in scene understanding for navigation tasks. Classical cameras suffer from motion blur in such scenarios rendering them effete. On the contrary, event cameras, because of…

Computer Vision and Pattern Recognition · Computer Science 2020-11-10 Chethan M. Parameshwara , Nitin J. Sanket , Chahat Deep Singh , Cornelia Fermüller , Yiannis Aloimonos

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

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

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

Event-based cameras, inspired by the biological retina, have evolved into cutting-edge sensors distinguished by their minimal power requirements, negligible latency, superior temporal resolution, and expansive dynamic range. At present,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Han Wang , Yuman Nie , Yun Li , Hongjie Liu , Min Liu , Wen Cheng , Yaoxiong Wang

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

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

Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in static or low-motion scenes, rigidly mounted event cameras are unable to generate any events…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Vincenzo Polizzi , Stephen Yang , Quentin Clark , Jonathan Kelly , Igor Gilitschenski , David B. Lindell

Event cameras are bio-inspired vision sensors that naturally capture the dynamics of a scene, filtering out redundant information. This paper presents a deep neural network approach that unlocks the potential of event cameras on a…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Ana I. Maqueda , Antonio Loquercio , Guillermo Gallego , Narciso Garcia , Davide Scaramuzza

Moving object segmentation plays a crucial role in understanding dynamic scenes involving multiple moving objects, while the difficulties lie in taking into account both spatial texture structures and temporal motion cues. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Zhexiong Wan , Bin Fan , Le Hui , Yuchao Dai , Gim Hee Lee
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