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Shape from Polarization (SfP) estimates surface normals using photos captured at different polarizer rotations. Fundamentally, the SfP model assumes that light is reflected either diffusely or specularly. However, this model is not valid…

Computer Vision and Pattern Recognition · Computer Science 2016-06-14 Vage Taamazyan , Achuta Kadambi , Ramesh Raskar

In this paper, we propose a novel projector-camera system for practical and low-cost acquisition of a dense object 3D model with the spectral reflectance property. In our system, we use a standard RGB camera and leverage an off-the-shelf…

Computer Vision and Pattern Recognition · Computer Science 2019-08-23 Chunyu Li , Yusuke Monno , Hironori Hidaka , Masatoshi Okutomi

The acquisition of high-resolution retinal fundus images with a large field of view (FOV) is challenging due to technological, physiological and economic reasons. This paper proposes a fully automatic framework to reconstruct retinal images…

Computer Vision and Pattern Recognition · Computer Science 2016-02-11 Thomas Köhler , Axel Heinrich , Andreas Maier , Joachim Hornegger , Ralf P. Tornow

This paper addresses the problem of reconstructing the surface shape of transparent objects. The difficulty of this problem originates from the viewpoint dependent appearance of a transparent object, which quickly makes reconstruction…

Image and Video Processing · Electrical Eng. & Systems 2021-05-24 Kai Han , Kwan-Yee K. Wong , Miaomiao Liu

Fine-detailed reconstructions are in high demand in many applications. However, most of the existing RGB-D reconstruction methods rely on pre-calculated accurate camera poses to recover the detailed surface geometry, where the…

Computer Vision and Pattern Recognition · Computer Science 2022-10-25 Lu Sang , Bjoern Haefner , Xingxing Zuo , Daniel Cremers

Feature detectors and descriptors are key low-level vision tools that many higher-level tasks build on. Unfortunately these fail in the presence of challenging light transport effects including partial occlusion, low contrast, and…

Computer Vision and Pattern Recognition · Computer Science 2019-01-15 Donald G. Dansereau , Bernd Girod , Gordon Wetzstein

We propose a learning-based depth from focus/defocus (DFF), which takes a focal stack as input for estimating scene depth. Defocus blur is a useful cue for depth estimation. However, the size of the blur depends on not only scene depth but…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Yuki Fujimura , Masaaki Iiyama , Takuya Funatomi , Yasuhiro Mukaigawa

This paper explores the problem of reconstructing high-resolution light field (LF) images from hybrid lenses, including a high-resolution camera surrounded by multiple low-resolution cameras. To tackle this challenge, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Jing Jin , Junhui Hou , Jie Chen , Sam Kwong , Jingyi Yu

Ptychography involves a sample being illuminated by a coherent, localised probe of illumination. When the probe interacts with the sample, the light is diffracted and a diffraction pattern is detected. Then the probe or sample is shifted…

Numerical Analysis · Mathematics 2023-05-09 Mark Philip Roach

In 3D face reconstruction, orthogonal projection has been widely employed to substitute perspective projection to simplify the fitting process. This approximation performs well when the distance between camera and face is far enough.…

Computer Vision and Pattern Recognition · Computer Science 2023-07-05 Yueying Kao , Bowen Pan , Miao Xu , Jiangjing Lyu , Xiangyu Zhu , Yuanzhang Chang , Xiaobo Li , Zhen Lei

High resolution reconstruction of complicated objects from incomplete and noisy data can be achieved by solving modulation equations iteratively under physical constraints. This direct demodulation method is a powerful technique for dealing…

Astrophysics · Physics 2009-11-10 Ti-Pei Li , Mei Wu

Non-line-of-sight (NLOS) imaging is based on capturing the multi-bounce indirect reflections from the hidden objects. Active NLOS imaging systems rely on the capture of the time of flight of light through the scene, and have shown great…

Image and Video Processing · Electrical Eng. & Systems 2022-04-19 Jiayong Peng , Fangzhou Mu , Ji Hyun Nam , Siddeshwar Raghavan , Yin Li , Andreas Velten , Zhiwei Xiong

Many imaging technologies rely on tomographic reconstruction, which requires solving a multidimensional inverse problem given a finite number of projections. Backprojection is a popular class of algorithm for tomographic reconstruction,…

Image and Video Processing · Electrical Eng. & Systems 2020-06-03 Xueqing Liu , Paul Sajda

Achieving high spatial resolution is the goal of many imaging systems. Designing a high-resolution lens with diffraction-limited performance over a large field of view remains a difficult task in imaging system design. On the other hand,…

This paper introduces a parametric level-set method for tomographic reconstruction of partially discrete images. Such images consist of a continuously varying background and an anomaly with a constant (known) grey-value. We represent the…

Computational Engineering, Finance, and Science · Computer Science 2020-12-15 Ajinkya Kadu , Tristan van Leeuwen , K. Joost Batenburg

Light Field (LF) offers unique advantages such as post-capture refocusing and depth estimation, but low-light conditions limit these capabilities. To restore low-light LFs we should harness the geometric cues present in different LF views,…

Image and Video Processing · Electrical Eng. & Systems 2020-12-29 Mohit Lamba , Kranthi Kumar , Kaushik Mitra

Inspired by the recent advances in implicitly representing signals with trained neural networks, we aim to learn a continuous representation for narrow-baseline 4D light fields. We propose an implicit representation model for 4D light…

Computer Vision and Pattern Recognition · Computer Science 2021-12-02 Paramanand Chandramouli , Hendrik Sommerhoff , Andreas Kolb

A set of orthonormal polynomials is proposed for image reconstruction from projection data. The relationship between the projection moments and image moments is discussed in detail, and some interesting properties are demonstrated.…

Computer Vision and Pattern Recognition · Computer Science 2014-03-14 Huazhong Shu , Jian Zhou , Guo-Niu Han , Limin M. Luo , Jean-Louis Coatrieux

We present a novel non-rigid reconstruction method using a moving RGB-D camera. Current approaches use only non-rigid part of the scene and completely ignore the rigid background. Non-rigid parts often lack sufficient geometric and…

Computer Vision and Pattern Recognition · Computer Science 2018-05-31 Shafeeq Elanattil , Peyman Moghadam , Sridha Sridharan , Clinton Fookes , Mark Cox

We present Neural Microfacet Fields, a method for recovering materials, geometry, and environment illumination from images of a scene. Our method uses a microfacet reflectance model within a volumetric setting by treating each sample along…

Computer Vision and Pattern Recognition · Computer Science 2023-10-18 Alexander Mai , Dor Verbin , Falko Kuester , Sara Fridovich-Keil
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