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Bayesian inference provides a principled way of estimating the parameters of a stochastic process that is observed discretely in time. The overdamped Brownian motion of a particle confined in an optical trap is generally modelled by the…

Data Analysis, Statistics and Probability · Physics 2017-02-01 Sudipta Bera , Shuvojit Paul , Rajesh Singh , Dipanjan Ghosh , Avijit Kundu , Ayan Banerjee , R. Adhikari

The scarcity of ground-truth labels poses one major challenge in developing optical flow estimation models that are both generalizable and robust. While current methods rely on data augmentation, they have yet to fully exploit the rich…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Jisoo Jeong , Hong Cai , Risheek Garrepalli , Jamie Menjay Lin , Munawar Hayat , Fatih Porikli

Optofluidic sensors based on highly dispersive two-dimensional photonic crystal waveguides are theoretically studied. Results show that these structures are strongly sensitive to the refractive index of the infiltrated liquid (nl), which is…

Optics · Physics 2011-11-10 Sanshui Xiao , Niels Asger Mortensen

This paper studies optical flow estimation, a critical task in motion analysis with applications in autonomous navigation, action recognition, and film production. Traditional optical flow methods require consecutive frames, which are often…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Mo Zhou , Jianwei Wang , Xuanmeng Zhang , Dylan Campbell , Kai Wang , Long Yuan , Wenjie Zhang , Xuemin Lin

High-Q optical resonators allow label-free detection of individual nanoparticles through perturbation of optical signatures but have practical limitations due to reliance on random diffusion to deliver particles to the sensing region. We…

Optics · Physics 2016-10-03 Jeewon Suh , Kewen Han , Christopher W Peterson , Gaurav Bahl

The primary goal of Optimal Power Flow (OPF) is to optimize the operation of a power system while meeting the demand and adhering to operational constraints. This paper presents a new approach for AC OPF. First, the approach constructs a…

Optimization and Control · Mathematics 2025-12-16 Mohammed N. Khamees , Kai Sun

To date, top-performing optical flow estimation methods only take pairs of consecutive frames into account. While elegant and appealing, the idea of using more than two frames has not yet produced state-of-the-art results. We present a…

Computer Vision and Pattern Recognition · Computer Science 2018-11-30 Zhile Ren , Orazio Gallo , Deqing Sun , Ming-Hsuan Yang , Erik B. Sudderth , Jan Kautz

The great potential of unsupervised monocular depth estimation has been demonstrated by many works due to low annotation cost and impressive accuracy comparable to supervised methods. To further improve the performance, recent works mainly…

Computer Vision and Pattern Recognition · Computer Science 2023-02-08 Junyu Zhu , Lina Liu , Yong Liu , Wanlong Li , Feng Wen , Hongbo Zhang

The development of optical nanofibers (ONF) and the study and control of their optical properties when coupling atoms to their electromagnetic modes has opened new possibilities for their use in quantum optics and quantum information…

The principle of optical trapping is conventionally based on the interaction of optical fields with linear induced polarizations. However, the optical force originating from the nonlinear polarization becomes significant when nonlinear…

Optics · Physics 2017-09-22 Liping Gong , Bing Gu , Guanghao Rui , Yiping Cui , Zhuqing Zhu , Qiwen Zhan

Modern optical flow methods make use of salient scene feature points detected and matched within the scene as a basis for sparse-to-dense optical flow estimation. Current feature detectors however either give sparse, non uniform point…

Computer Vision and Pattern Recognition · Computer Science 2019-05-21 Felix Stephenson , Toby Breckon , Ioannis Katramados

Motion representation plays a vital role in human action recognition in videos. In this study, we introduce a novel compact motion representation for video action recognition, named Optical Flow guided Feature (OFF), which enables the…

Computer Vision and Pattern Recognition · Computer Science 2018-07-10 Shuyang Sun , Zhanghui Kuang , Wanli Ouyang , Lu Sheng , Wei Zhang

Recent works on optical flow estimation use neural networks to predict the flow field that maps positions of one image to positions of the other. These networks consist of a feature extractor, a correlation volume, and finally several…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Leyla Mirvakhabova , Hong Cai , Jisoo Jeong , Hanno Ackermann , Farhad Zanjani , Fatih Porikli

Normalizing flows (NFs) have become a prominent method for deep generative models that allow for an analytic probability density estimation and efficient synthesis. However, a flow-based network is considered to be inefficient in parameter…

Machine Learning · Computer Science 2020-10-26 Sang-gil Lee , Sungwon Kim , Sungroh Yoon

This study introduces an experimental teaching method that employs optic fiber interferometry (OFI) to investigate forced vibration phenomena. It is designed for undergraduate physics majors with foundational mechanics and optics training…

Physics Education · Physics 2025-04-22 Mingyuan Wang , Manli Zhou , Hengda Ji , Tao Lan

This paper introduces a new method for inter-frame coding based on two complementary autoencoders: MOFNet and CodecNet. MOFNet aims at computing and conveying the Optical Flow and a pixel-wise coding Mode selection. The optical flow is used…

Image and Video Processing · Electrical Eng. & Systems 2020-08-07 Théo Ladune , Pierrick Philippe , Wassim Hamidouche , Lu Zhang , Olivier Déforges

We systematically compare and analyze a set of key components in unsupervised optical flow to identify which photometric loss, occlusion handling, and smoothness regularization is most effective. Alongside this investigation we construct a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-17 Rico Jonschkowski , Austin Stone , Jonathan T. Barron , Ariel Gordon , Kurt Konolige , Anelia Angelova

Manipulating fluids by light at the nanoscale has been a long-sought-after goal for lab-on-a-chip applications. Plasmonic heating has been demonstrated to control microfluidic dynamics due to the enhanced and confined light absorption from…

Optics · Physics 2023-08-01 Sen Yang , Justus C. Ndukaife

The evanescent field outside an optical nanofiber (ONF) can create optical traps for neutral atoms. We present a non-destructive method to characterize such trapping potentials. An off-resonance linearly polarized probe beam that propagates…

Quantum Physics · Physics 2017-06-09 Pablo Solano , Fredrik K. Fatemi , Luis A. Orozco , S. L. Rolston

We present a position- and time-dependent optical force theory for optomechanics of dispersive 3D photonic materials and devices. The theory applies to media including material interfaces, waveguides, and general photonic crystal…

Optics · Physics 2022-07-22 Mikko Partanen , Jukka Tulkki