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3d-reconstruction-by-gf-4

Part of implementation of paper named Determining Both Surface Position and Orientation in Structured-Light-Based Sensing. Its abstract is Position and orientation profiles are two principal descriptions of shape in space. We describe how a structured light system, coupled with the illumination of a pseudorandom pattern and a suitable choice of feature points, can allow not only the position but also the orientation of individual surface elements to be determined independently. Unlike traditional designs which use the centroids of the illuminated pattern elements as the feature points, the proposed design uses the grid points between the pattern elements instead. The grid points have the essences that their positions in the image data are inert to the effect of perspective distortion, their individual extractions are not directly dependent on one another, and the grid points possess strong symmetry that can be exploited for their precise localization in the image data. Most importantly, the grid lines of the illuminated pattern that form the grid points can aid in determining surface normals. In this paper, we describe how each of the grid points can be labeled with a unique color code, what symmetry they possess and how the symmetry can be exploited for their precise localization at subpixel accuracy in the image data, and how 3D orientation in addition to 3D position can be determined at each of them. Both the position and orientation profiles can be determined with only a single pattern illumination and a single image capture. And the doi of the paper is 10.1109/TPAMI.2009.192.

3dcs

Three-dimensional compressive sensing algorithms

3dshearlet

3D discrete shearlet

3dv_tutorial

An Invitation to 3D Vision: A Tutorial for Everyone

adaptive-grayscale-csi-blue-noise-patterns

Simulation codes for "Adaptive Grayscale Compressive Spectral Imaging Using Optimal Blue Noise Coding Patterns"

aditof_sdk

Analog Devices 3D ToF software suite

admm-diptv

Combining Weighted Total Variation and Deep Image Prior for natural and medical image restoration via ADMM (2021)

an-efficient-algorithm-designing-robust-projection-matrix

An Efficient Algorithm Designing Robust Projection Matrix

auto-6ml

Auto^6ML is a jittor library allowing users to achieve machine learning automation.

awesome

😎 Awesome lists about all kinds of interesting topics

awesome-cvpr2023-low-level-vision

A Collection of Papers and Codes in CVPR2023/2022 about low level vision

awesome-state-space-models

Collection of papers on state-space models

awesome-transformer-attention

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

awesome-vision-attentions

Summary of related papers on visual attention. Related code will be released based on Jittor gradually.

birnat

block-based-cs-nns

Block-Based Compressed Sensing using NNs

bluenoisedithermasktiles

Utility for producing blue-noise dither mask tiles on the GPU

bluenoisegenerator

burnwoundareaanalysis

c

All Algorithms implemented in C

c-plus-plus

All Algorithms implemented in C++

cassi-self-supervised

cilib

Code for the book "Compressive imaging: Structure, Sampling, Learning".

color-coded-aperture

Depth from a Calibrated Color-Coded Aperture Camera using Disparity

compressive-sensing-denoising

Compressed sensing and denoising of images using sparse representations

computervision-recipes

Best Practices, code samples, and documentation for Computer Vision.

cs-mcnet

Pytorch code of CS-MCNet

cs-with-prior-information

This repository provides a Matlab implementation of the ADMM-based solvers for L1-L1 and L1-L2 minimization.

d2l-zh-tensorflow-colab

Automatically Generated d2l-zh TensorFlow Notebooks for Colab

deep-compressed-sensing

Deep Learning/Deep neural network-based Image/Video (Quantized) Compressed/Compressive Sensing (Coding)