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Accessing and characterizing a flow impose a number of constraints on the employed measurement techniques; in particular optical methods require transparent fluids and windows in the vessel. Whereas one can adapt apparatus, fluid and…

Video anomaly detection is a challenging task because of diverse abnormal events. To this task, methods based on reconstruction and prediction are wildly used in recent works, which are built on the assumption that learning on normal data,…

Computer Vision and Pattern Recognition · Computer Science 2021-05-11 Hongyong Wang , Xinjian Zhang , Su Yang , Weishan Zhang

Real-time motion detection in non-stationary scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource. These challenges degrade the performance of the existing methods in…

Computer Vision and Pattern Recognition · Computer Science 2018-11-22 Junjie Huang , Wei Zou , Zheng Zhu , Jiagang Zhu

We explore the application of the reference map technique, originally developed for the Eulerian simulation of solid mechanics, in Lagrangian kinematics of fluid flows. Unlike traditional methods based on explicit particle tracking, the…

Fluid Dynamics · Physics 2024-12-04 Imran Hayat , Ryan T. Black , George Ilhwan Park

Fluid deformation and strain history are central to wide range of fluid mechanical phenomena ranging from fluid mixing and particle transport to stress development in complex fluids and the formation of Lagrangian coherent structures…

Fluid Dynamics · Physics 2025-10-03 Daniel R. Lester , Marco Dentz , Tanguy Le Borgne , Felipe P. J. de Barros

The human ability to detect and segment moving objects works in the presence of multiple objects, complex background geometry, motion of the observer, and even camouflage. In addition to all of this, the ability to detect motion is nearly…

Computer Vision and Pattern Recognition · Computer Science 2016-04-04 Pia Bideau , Erik Learned-Miller

Optical flow estimation remains challenging due to untextured areas, motion boundaries, occlusions, and more. Thus, the estimated flow is not equally reliable across the image. To that end, post-hoc confidence measures have been introduced…

Computer Vision and Pattern Recognition · Computer Science 2017-08-23 Anne S. Wannenwetsch , Margret Keuper , Stefan Roth

Optical flow estimation is a well-studied topic for automated driving applications. Many outstanding optical flow estimation methods have been proposed, but they become erroneous when tested in challenging scenarios that are commonly…

Computer Vision and Pattern Recognition · Computer Science 2023-01-12 Shihao Shen , Louis Kerofsky , Senthil Yogamani

Optical flow computation with frame-based cameras provides high accuracy but the speed is limited either by the model size of the algorithm or by the frame rate of the camera. This makes it inadequate for high-speed applications. Event…

Computer Vision and Pattern Recognition · Computer Science 2022-07-25 Ashwin Sanjay Lele , Arijit Raychowdhury

We present in this article a novel Lagrangian measurement technique: an instrumented particle which continuously transmits the force/acceleration acting on it as it is advected in a flow. We develop signal processing methods to extract…

Event cameras such as DAVIS can simultaneously output high temporal resolution events and low frame-rate intensity images, which own great potential in capturing scene motion, such as optical flow estimation. Most of the existing optical…

Computer Vision and Pattern Recognition · Computer Science 2022-11-18 Zhexiong Wan , Yuchao Dai , Yuxin Mao

The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view…

Computer Vision and Pattern Recognition · Computer Science 2019-11-25 Katrin Lasinger , Christoph Vogel , Thomas Pock , Konrad Schindler

In this paper, two simple principal component regression methods for estimating the optical flow between frames of video sequences according to a pel-recursive manner are introduced. These are easy alternatives to dealing with mixtures of…

Computer Vision and Pattern Recognition · Computer Science 2016-11-09 Felipe P. do Carmo , Vania Vieira Estrela , Joaquim Teixeira de Assis

Eyeframe lens tracing is an important process in the optical industry that requires sub-millimeter precision to ensure proper lens fitting and optimal vision correction. Traditional frame tracers rely on mechanical tools that need precise…

Computer Vision and Pattern Recognition · Computer Science 2026-02-19 Manel Guzmán , Antonio Agudo

Optical flow techniques are becoming increasingly performant and robust when estimating motion in a scene, but their performance has yet to be proven in the area of facial expression recognition. In this work, a variety of optical flow…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Benjamin Allaert , Isaac Ronald Ward , Ioan Marius Bilasco , Chaabane Djeraba , Mohammed Bennamoun

Accurately predicting the future fluid is vital to extensive areas such as meteorology, oceanology, and aerodynamics. However, since the fluid is usually observed from the Eulerian perspective, its moving and intricate dynamics are…

Machine Learning · Computer Science 2024-11-05 Qilong Ma , Haixu Wu , Lanxiang Xing , Shangchen Miao , Mingsheng Long

Optical imaging is commonly used for both scientific and technological applications across industry and academia. In image sensing, a measurement, such as of an object's position, is performed by computational analysis of a digitized image.…

The aim of the present paper is to introduce and to discuss inconsistencies errors that may arise when Eulerian and Lagrangian models are coupled for the simulations of turbulent poly-dispersed two-phase flows. In these hydrid models, two…

Fluid Dynamics · Physics 2011-04-07 Sergio Chibbaro , Jean-Pierre Minier

Standard frame-based cameras that sample light intensity frames are heavily impacted by motion blur for high-speed motion and fail to perceive scene accurately when the dynamic range is high. Event-based cameras, on the other hand, overcome…

Computer Vision and Pattern Recognition · Computer Science 2021-03-22 Chankyu Lee , Adarsh Kumar Kosta , Kaushik Roy

Event cameras rely on motion to obtain information about scene appearance. This means that appearance and motion are inherently linked: either both are present and recorded in the event data, or neither is captured. Previous works treat the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Shuang Guo , Friedhelm Hamann , Guillermo Gallego