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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

In this paper, we propose a new approach for keypoint-based object detection. Traditional keypoint-based methods consist in classifying individual points and using pose estimation to discard misclassifications. Since a single point carries…

Computer Vision and Pattern Recognition · Computer Science 2009-02-02 Marcelo Hashimoto , Roberto M. Cesar

Event-based vision has been rapidly growing in recent years justified by the unique characteristics it presents such as its high temporal resolutions (~1us), high dynamic range (>120dB), and output latency of only a few microseconds. This…

Computer Vision and Pattern Recognition · Computer Science 2023-01-03 Zaid El-Shair , Samir Rawashdeh

Pose estimation and tracking of objects is a fundamental application in 3D vision. Event cameras possess remarkable attributes such as high dynamic range, low latency, and resilience against motion blur, which enables them to address…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Zibin Liu , Banglei Guan , Yang Shang , Qifeng Yu , Laurent Kneip

Event-based cameras are bio-inspired sensors that capture brightness change of every pixel in an asynchronous manner. Compared with frame-based sensors, event cameras have microsecond-level latency and high dynamic range, hence showing…

Computer Vision and Pattern Recognition · Computer Science 2023-03-20 Dongsheng Wang , Xu Jia , Yang Zhang , Xinyu Zhang , Yaoyuan Wang , Ziyang Zhang , Dong Wang , Huchuan Lu

We describe a method for visual object detection based on an ensemble of optimized decision trees organized in a cascade of rejectors. The trees use pixel intensity comparisons in their internal nodes and this makes them able to process…

Computer Vision and Pattern Recognition · Computer Science 2014-08-20 Nenad Markuš , Miroslav Frljak , Igor S. Pandžić , Jörgen Ahlberg , Robert Forchheimer

With the success of deep learning, object recognition systems that can be deployed for real-world applications are becoming commonplace. However, inference that needs to largely take place on the `edge' (not processed on servers), is a…

Computer Vision and Pattern Recognition · Computer Science 2020-01-30 Andres Ussa , Luca Della Vedova , Vandana Reddy Padala , Deepak Singla , Jyotibdha Acharya , Charles Zhang Lei , Garrick Orchard , Arindam Basu , Bharath Ramesh

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

In this work, we propose an edge detection algorithm by estimating a lifetime of an event produced from dynamic vision sensor (DVS), also known as event camera. The event camera, unlike traditional CMOS camera, generates sparse event data…

Robotics · Computer Science 2019-07-18 Sangil Lee , Haram Kim , H. Jin Kim

Event cameras are a cutting-edge type of visual sensors that capture data by detecting brightness changes at the pixel level asynchronously. These cameras offer numerous benefits over conventional cameras, including high temporal…

Multimedia · Computer Science 2024-11-12 Ahmadreza Sezavar , Catarina Brites , Joao Ascenso

Object pose tracking is one of the pivotal technologies in multimedia, attracting ever-growing attention in recent years. Existing methods employing traditional cameras encounter numerous challenges such as motion blur, sensor noise,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Zibin Liu , Banglei Guan , Yang Shang , Shunkun Liang , Zhenbao Yu , Qifeng Yu

Event cameras provide microsecond-level temporal resolution, low latency, and high dynamic range, offering potential for perception under fast motion and challenging illumination conditions. However, existing Event-based Object Detection…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Meisen Wang , Hao Deng , Wei Bao , Ma Yuanxiao , Chengjie Wang , Zhiqiang Tian , Shaoyi Du , Siqi Li

With several advantages over conventional RGB cameras, event cameras have provided new opportunities for tackling visual tasks under challenging scenarios with fast motion, high dynamic range, and/or power constraint. Yet unlike image/video…

Computer Vision and Pattern Recognition · Computer Science 2020-12-02 Srutarshi Banerjee , Zihao W. Wang , Henry H. Chopp , Oliver Cossairt , Aggelos Katsaggelos

Event cameras have higher temporal resolution, and require less storage and bandwidth compared to traditional RGB cameras. However, due to relatively lagging performance of event-based approaches, event cameras have not yet replace…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Muhammad Ahmed Ullah Khan , Abdul Hannan Khan , Andreas Dengel

Contrary to other standard cameras, event cameras interpret the world in an entirely different manner; as a collection of asynchronous events. Despite event camera's unique data output, many event feature detection and tracking algorithms…

Computer Vision and Pattern Recognition · Computer Science 2022-07-21 Sumin Hu , Yeeun Kim , Hyungtae Lim , Alex Junho Lee , Hyun Myung

Event cameras are novel sensors that report brightness changes in the form of asynchronous "events" instead of intensity frames. They have significant advantages over conventional cameras: high temporal resolution, high dynamic range, and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-18 Henri Rebecq , René Ranftl , Vladlen Koltun , 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,…

Line segment extraction is effective for capturing geometric features of human-made environments. Event-based cameras, which asynchronously respond to contrast changes along edges, enable efficient extraction by reducing redundant data.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Mikihiro Ikura , Arren Glover , Masayoshi Mizuno , Chiara Bartolozzi

In this work, we propose a motion robust and high-speed detection pipeline which better leverages the event data. First, we design an event stream representation called temporal active focus (TAF), which efficiently utilizes the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-27 Bingde Liu , Chang Xu , Wen Yang , Huai Yu , Lei Yu

Surveillance system (SS) development requires hi-tech support to prevail over the shortcomings related to the massive quantity of visual information from SSs. Anything but reduced human monitoring became impossible by means of its physical…

Computer Vision and Pattern Recognition · Computer Science 2016-10-11 Alessandra Martins Coelho , Vania V. Estrela