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Event cameras are bio-inspired sensors providing significant advantages over standard cameras such as low latency, high temporal resolution, and high dynamic range. We propose a novel structured-light system using an event camera to tackle…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Manasi Muglikar , Guillermo Gallego , Davide Scaramuzza

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 activity-driven bio-inspired vision sensors, thereby resulting in advantages such as sparsity,high temporal resolution, low latency, and power consumption. Given the different sensing modality of event camera and high…

Computer Vision and Pattern Recognition · Computer Science 2021-05-11 Lakshmi Annamalai , Vignesh Ramanathan , Chetan Singh Thakur

A new time-delay estimation (TDE) technique based on dynamic programming is developed, to measures the time-varying time-delay between two signals. Dynamic programming based TDE technique provides a frequency response 5 to 10 times higher…

Plasma Physics · Physics 2010-01-11 Deepak K. Gupta , George R. McKee , Raymond R. Fonck

A discrete-event simulation (DES) involves the execution of a sequence of event handlers dynamically scheduled at runtime. As a consequence, a priori knowledge of the control flow of the overall simulation program is limited. In particular,…

Performance · Computer Science 2018-05-14 Marc Leinweber , Hannes Hartenstein , Philipp Andelfinger

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

Transformer-based methods have achieved impressive results in time series forecasting. However, existing Transformers still exhibit limitations in sequence modeling as they tend to overemphasize temporal dependencies. This incurs additional…

Machine Learning · Computer Science 2025-12-16 Tan Wang , Yun Wei Dong , Qi Wang

Temporal Video Frame Synthesis (TVFS) aims at synthesizing novel frames at timestamps different from existing frames, which has wide applications in video codec, editing and analysis. In this paper, we propose a high framerate TVFS…

Computer Vision and Pattern Recognition · Computer Science 2019-07-09 Zihao W. Wang , Weixin Jiang , Kuan He , Boxin Shi , Aggelos Katsaggelos , Oliver Cossairt

Event cameras operate fundamentally differently from traditional Active Pixel Sensor (APS) cameras, offering significant advantages. Recent research has developed simulators to convert video frames into events, addressing the shortage of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Xiao Jiang , Fei Zhou , Jiongzhi Lin

Timed Transition Models (TTMs) are event-based descriptions for modelling, specifying, and verifying discrete real-time systems. An event can be spontaneous, fair, or timed with specified bounds. TTMs have a textual syntax, an operational…

Software Engineering · Computer Science 2015-06-12 Chen-Wei Wang , Jonathan S. Ostroff , Simon Hudon

Recent learning-based methods for event-based optical flow estimation utilize cost volumes for pixel matching but suffer from redundant computations and limited scalability to higher resolutions for flow refinement. In this work, we take…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Daikun Liu , Lei Cheng , Teng Wang , changyin Sun

Automated event detection has emerged as one of the fundamental practices to monitor the behavior of technical systems by means of sensor data. In the automotive industry, these methods are in high demand for tracing events in time series…

Machine Learning · Computer Science 2023-10-18 Bahareh Medghalchi , Andreas Vogel

Event cameras are novel sensors that perceive the per-pixel intensity changes and output asynchronous event streams with high dynamic range and less motion blur. It has been shown that events alone can be used for end-task learning, e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2021-11-25 Lin Wang , Yujeong Chae , Kuk-Jin Yoon

In recent years, there has been a growing interest in realizing methodologies to integrate more and more computation at the level of the image sensor. The rising trend has seen an increased research interest in developing novel event…

Image and Video Processing · Electrical Eng. & Systems 2021-05-05 Md Jubaer Hossain Pantho , Joel Mandebi Mbongue , Pankaj Bhowmik , Christophe Bobda

This paper presents a spatiotemporal unsupervised feature learning method for cause identification of electromagnetic transient events (EMTE) in power grids. The proposed method is formulated based on the availability of time-synchronized…

Signal Processing · Electrical Eng. & Systems 2019-03-13 Iman Niazazari , Reza Jalilzadeh Hamidi , Hanif Livani , Reza Arghandeh

Event cameras are dynamic vision sensors inspired by the biological retina, characterized by their high dynamic range, high temporal resolution, and low power consumption. These features make them capable of perceiving 3D environments even…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Hoonhee Cho , Jae-Young Kang , Kuk-Jin Yoon

Event camera has offered promising alternative for visual perception, especially in high speed and high dynamic range scenes. Recently, many deep learning methods have shown great success in providing promising solutions to many event-based…

Computer Vision and Pattern Recognition · Computer Science 2022-04-06 Ziluo Ding , Rui Zhao , Jiyuan Zhang , Tianxiao Gao , Ruiqin Xiong , Zhaofei Yu , Tiejun Huang

Event-based cameras are bio-inspired vision sensors whose pixels work independently from each other and respond asynchronously to brightness changes, with microsecond resolution. Their advantages make it possible to tackle challenging…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Yi Zhou , Guillermo Gallego , Shaojie Shen

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

Keyword spotting in edge devices is becoming increasingly important as voice-activated assistants are widely used. However, its deployment is often limited by the extreme low-power constraints of the target embedded systems. Here, we…

Neural and Evolutionary Computing · Computer Science 2025-03-20 Alejandro Pequeño-Zurro , Lyes Khacef , Stefano Panzeri , Elisabetta Chicca