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Code minimization provides a speed-up of the processing time of fringe projection based stereo sensors and possibly makes them real-time applicable. This paper reports a methodology which enables such sensors to completely omit Gray code or…

Metric Geometry · Mathematics 2014-04-30 Christian Bräuer-Burchardt , Peter Kühmstedt , Gunther Notni

Event cameras are novel bio-inspired sensors that measure per-pixel brightness differences asynchronously. Recovering brightness from events is appealing since the reconstructed images inherit the high dynamic range (HDR) and high-speed…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Zelin Zhang , Anthony Yezzi , Guillermo Gallego

For quantitative evaluation of sleep disturbances, a noninvasive monitoring system is developed by introducing an event-based method. We observe sleeping in home context and classify the sleep disturbances into three types of events: motion…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Lyn Chao-ling Chen , Kuan-Wen Chen , Yi-Ping Hung

Active range sensing using structured-light is the most accurate and reliable method for obtaining 3D information. However, most of the work has been limited to range sensing of static objects, and range sensing of dynamic (moving or…

Computer Vision and Pattern Recognition · Computer Science 2015-09-15 Changsoo Je , Sang Wook Lee , Rae-Hong Park

Event-based cameras capture visual information as asynchronous streams of per-pixel brightness changes, generating sparse, temporally precise data. Compared to conventional frame-based sensors, they offer significant advantages in capturing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Biswadeep Sen , Benoit R. Cottereau , Nicolas Cuperlier , Terence Sim

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

Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate downstream image processing, especially for complex tasks such…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Darryl Hannan , Ragib Arnab , Gavin Parpart , Garrett T. Kenyon , Edward Kim , Yijing Watkins

Event cameras provide microsecond latency, making them suitable for 6D object pose tracking in fast, dynamic scenes where conventional RGB and depth pipelines suffer from motion blur and large pixel displacements. We introduce EventTrack6D,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jae-Young Kang , Hoonhee Cho , Taeyeop Lee , Minjun Kang , Bowen Wen , Youngho Kim , Kuk-Jin Yoon

3D Gaussian Splatting (3D-GS) has demonstrated exceptional capabilities in 3D scene reconstruction and novel view synthesis. However, its training heavily depends on high-quality, sharp images and accurate camera poses. Fulfilling these…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Wangbo Yu , Chaoran Feng , Jiye Tang , Jiashu Yang , Zhenyu Tang , Xu Jia , Yuchao Yang , Li Yuan , Yonghong Tian

Event cameras are a new type of image sensors that output changes in light intensity (events) instead of absolute intensity values. They have a very high temporal resolution and a high dynamic range. In this paper, we propose a method to…

Computer Vision and Pattern Recognition · Computer Science 2021-03-23 Hamid Sarmadi , Rafael Muñoz-Salinas , Miguel A. Olivares-Mendez , Rafael Medina-Carnicer

Depth estimation is a critical task in computer vision, with applications in autonomous navigation, robotics, and augmented reality. Event cameras, which encode temporal changes in light intensity as asynchronous binary spikes, offer unique…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Xin Zhang , Liangxiu Han , Tam Sobeih , Lianghao Han , Darren Dancey

Event sensors output a stream of asynchronous brightness changes (called ``events'') at a very high temporal rate. Previous works on recovering the lost intensity information from the event sensor data have heavily relied on the event…

Computer Vision and Pattern Recognition · Computer Science 2020-03-18 Prasan A Shedligeri , Kaushik Mitra

Event-based cameras are novel, efficient sensors inspired by the human vision system, generating an asynchronous, pixel-wise stream of data. Learning from such data is generally performed through heavy preprocessing and event integration…

Computer Vision and Pattern Recognition · Computer Science 2020-04-08 Giorgio Giannone , Asha Anoosheh , Alessio Quaglino , Pierluca D'Oro , Marco Gallieri , Jonathan Masci

The stereo-matching problem, i.e., matching corresponding features in two different views to reconstruct depth, is efficiently solved in biology. Yet, it remains the computational bottleneck for classical machine vision approaches. By…

Computer Vision and Pattern Recognition · Computer Science 2021-04-07 Nicoletta Risi , Enrico Calabrese , Giacomo Indiveri

Compared to conventional cameras, event cameras provide a high dynamic range and low latency, offering greater robustness to rapid motion and challenging lighting conditions. Although the potential of event cameras for visual place…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Therese Joseph , Tobias Fischer , Michael Milford

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 cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". The innovative way they acquire data presents several advantages over standard devices, especially in poor…

Computer Vision and Pattern Recognition · Computer Science 2021-11-01 Mirco Planamente , Chiara Plizzari , Marco Cannici , Marco Ciccone , Francesco Strada , Andrea Bottino , Matteo Matteucci , Barbara Caputo

We propose a novel dense mapping framework for sparse visual SLAM systems which leverages a compact scene representation. State-of-the-art sparse visual SLAM systems provide accurate and reliable estimates of the camera trajectory and…

Computer Vision and Pattern Recognition · Computer Science 2021-07-20 Hidenobu Matsuki , Raluca Scona , Jan Czarnowski , Andrew J. Davison

Capturing and reconstructing high-speed dynamic 3D scenes has numerous applications in computer graphics, vision, and interdisciplinary fields such as robotics, aerodynamics, and evolutionary biology. However, achieving this using a single…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Zihao Zou , Ziyuan Qu , Xi Peng , Vivek Boominathan , Adithya Pediredla , Praneeth Chakravarthula

Emerging event cameras acquire visual information by detecting time domain brightness changes asynchronously at the pixel level and, unlike conventional cameras, are able to provide high temporal resolution, very high dynamic range, low…

Multimedia · Computer Science 2024-11-06 Ahmadreza Sezavar , Catarina Brites , Joao Ascenso
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