hySLAM is a hybrid SLAM/SfM system designed for mapping

Related tags

Deep Learninghyslam
Overview

HySLAM Overview

hySLAM is a hybrid SLAM/SfM system designed for mapping. The system is based on ORB-SLAM2 with some modifications and refactoring.

Raúl Mur-Artal and Juan D. Tardós. ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras. IEEE Transactions on Robotics, vol. 33, no. 5, pp. 1255-1262, 2017.

ORB-SLAM2 original code: ORB-SLAM2_repo

Modifications:

  1. Support for multiple cameras.
  2. Addition of a Multi-map, recursive data structure: a recursive tree structure is used to handle sub-maps. Sub-maps can be optionally registered with their parent to make keyframes and map points accessible to the parent or the sub-map can be kept private
  3. Trajectory tracking: Per-frame camera trajectories are explicitly recorded as SE(3) transformations relative to reference keyframes, whose positions are continuously updated via optimization
  4. Extensive code refactoring including converting Tracking to a state-machine, conversion of Mapping to a job based, parallel module, and addition of a separate Feature Extraction thread.

Example Use

hySLAM was used as the basis for a dual-camera SLAM system to map visually repetitive ecosystems such as grasslands, where conventional Strucuture from Motion techniques are unreliable. The dual-camera SLAM system uses a forward-facing stereocamera to provide localization information while a downward facing high-resolution "documentation" camera is used to record the ecosystem. Conventional SLAM is used to analyze the forward-facing stereocamera video. The trajectory of the stereocamera is then used to guide localization and mapping from the documentation camera as illustrated in the figure below: dc_overview

The dual-camera SLAM system allows reliable mapping of repetitive ecosystems as illustrated below: recon_examples A: Accurately reconstructed campus lawn using dual camera SLAM. B: SfM failure due to visual aliasing (blue squares represent aligned images). The three lines of images (highlighted in red) should be parallel but instead converge on a single point in the reconstruction

Dependencies:

  1. pangolin
  2. DBoW2
  3. OpenCV

Installation

  1. in Thirdparty, compile and install g2o: cmake .. make -jX sudo make install sudo ldconfig
  2. compile and install hyslam in main CMakeLists set opencv directory cmake .. make -jX sudo make install
  3. build binary vocabulary: ./tools/bin_vocabulary
Owner
Brian Hopkinson
Associate Professor, Applications of Computer Vision and Machine Learning to Environmental Science
Brian Hopkinson
Deformable DETR is an efficient and fast-converging end-to-end object detector.

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

2k Jan 05, 2023
The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"

Swin-Unet The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"(https://arxiv.org/abs/2105.05537). A validatio

869 Jan 07, 2023
COVID-VIT: Classification of Covid-19 from CT chest images based on vision transformer models

COVID-ViT COVID-VIT: Classification of Covid-19 from CT chest images based on vision transformer models This code is to response to te MIA-COV19 compe

17 Dec 30, 2022
A TensorFlow implementation of DeepMind's WaveNet paper

A TensorFlow implementation of DeepMind's WaveNet paper This is a TensorFlow implementation of the WaveNet generative neural network architecture for

Igor Babuschkin 5.3k Dec 28, 2022
SGPT: Multi-billion parameter models for semantic search

SGPT: Multi-billion parameter models for semantic search This repository contains code, results and pre-trained models for the paper SGPT: Multi-billi

Niklas Muennighoff 182 Dec 29, 2022
Implementation of Bagging and AdaBoost Algorithm

Bagging-and-AdaBoost Implementation of Bagging and AdaBoost Algorithm Dataset Red Wine Quality Data Sets For simplicity, we will have 2 classes of win

Zechen Ma 1 Nov 01, 2021
JstDoS - HTTP Protocol Stack Remote Code Execution Vulnerability

jstDoS If you are going to skid that, please give credits ! ^^ ¿How works? This

apolo 4 Feb 11, 2022
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

Build Type Linux MacOS Windows Build Status OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facia

25.7k Jan 09, 2023
Codes for CyGen, the novel generative modeling framework proposed in "On the Generative Utility of Cyclic Conditionals" (NeurIPS-21)

On the Generative Utility of Cyclic Conditionals This repository is the official implementation of "On the Generative Utility of Cyclic Conditionals"

Chang Liu 44 Nov 16, 2022
Graduation Project

Gesture-Detection-and-Depth-Estimation This is my graduation project. (1) In this project, I use the YOLOv3 object detection model to detect gesture i

ChaosAT 1 Nov 23, 2021
Implementation of the paper All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training

SemCo The official pytorch implementation of the paper All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training

42 Nov 14, 2022
Colar: Effective and Efficient Online Action Detection by Consulting Exemplars, CVPR 2022.

Colar: Effective and Efficient Online Action Detection by Consulting Exemplars This repository is the official implementation of Colar. In this work,

LeYang 246 Dec 13, 2022
This is a project based on ConvNets used to identify whether a road is clean or dirty. We have used MobileNet as our base architecture and the weights are based on imagenet.

PROJECT TITLE: CLEAN/DIRTY ROAD DETECTION USING TRANSFER LEARNING Description: This is a project based on ConvNets used to identify whether a road is

Faizal Karim 3 Nov 06, 2022
On-device speech-to-index engine powered by deep learning.

On-device speech-to-index engine powered by deep learning.

Picovoice 30 Nov 24, 2022
Code for our ICCV 2021 Paper "OadTR: Online Action Detection with Transformers".

Code for our ICCV 2021 Paper "OadTR: Online Action Detection with Transformers".

66 Dec 15, 2022
Pytorch implementation of PTNet for high-resolution and longitudinal infant MRI synthesis

Pyramid Transformer Net (PTNet) Project | Paper Pytorch implementation of PTNet for high-resolution and longitudinal infant MRI synthesis. PTNet: A Hi

Xuzhe Johnny Zhang 6 Jun 08, 2022
Embracing Single Stride 3D Object Detector with Sparse Transformer

SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer

TuSimple 385 Dec 28, 2022
Supervised forecasting of sequential data in Python.

Supervised forecasting of sequential data in Python. Intro Supervised forecasting is the machine learning task of making predictions for sequential da

The Alan Turing Institute 54 Nov 15, 2022
OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021)

OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021) Video demo We here provide a video demo from co

20 Nov 25, 2022
[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

FedBN: Federated Learning on Non-IID Features via Local Batch Normalization This is the PyTorch implemention of our paper FedBN: Federated Learning on

<a href=[email protected]"> 156 Dec 15, 2022