SE3 Pose Interp - Interpolate camera pose or trajectory in SE3, pose interpolation, trajectory interpolation

Overview

SE3 Pose Interpolation

Pose estimated from SLAM system are always discrete, and often not equal to the original sequence frame size.

This repo helps to remedy it and interpolate the pose for any interval timestamp you want.

p_interp_demo

Dependencies & Environment

The repo has minimal requirement:

python==3.7
numpy==1.19
transformations==2021.6.6
evo==v1.13.5

How to Run

The script takes two files as input data, keyframe pose and lookup timestamps, the lookup timestamps contains much more timestamps data than keyframe sequences.

To run this script simply try:

python pose_interp.py --kf_pose ./data/kf_pose_result_tum.txt \
                      --timestamps ./data/timestamps.txt

The output file will be saved at the same directory with extra suffix _interp.txt

File format

Please make sure the estimated key-frame pose file (e.g.: ./data/kf_pose_result_tum.txt) is in TUM format:

timestamp t_x t_y t_z q_x q_y q_z q_w

The timestamps file for all frames (e.g.: ./data/timestamps.txt) is saved as following:

sequence_id timestamp

The output interpolated pose file which contains pose for each timestamp of every frame in the original sequence (e.g.: ./data/kf_pose_result_tum_interp.txt) is also in TUM format:

timestamp t_x t_y t_z q_x q_y q_z q_w

Visualization

We use evo to visualize the pose file, simply run the following code to get the plots

pose_interp

To run the visualization code, please try:

python pose_vis.py --kf_pose ./data/kf_pose_result_tum_vis.txt --full_pose ./data/kf_pose_result_tum_interp.txt

Please note that file kf_pose_result_tum_vis.txt is downsampled from original keyframe sequence kf_pose_result_tum_vis.txt for better visualization effect.

Disclaimer

This repo is adapted from https://github.com/ethz-asl/robotcar_tools/blob/master/python/interpolate_poses.py

The modification includes:

  • fixed axis align mis-match bug
  • add visualization for sanity check
  • consistent data format with clear comments
  • loop up any given interval timestamp

If you use part of this code please cite:

@software{cheng2022poseinterp,
  author = {Lisa, Mona and Bot, Hew},
  doi = {10.5281/zenodo.1234},
  month = {12},
  title = {{SE3 Pose Interpolation Toolbox}},
  url = {https://github.com/rancheng/se3_pose_interp},
  version = {1.0.0},
  year = {2022}
}

and

@article{RobotCarDatasetIJRR,
  Author = {Will Maddern and Geoff Pascoe and Chris Linegar and Paul Newman},
  Title = {{1 Year, 1000km: The Oxford RobotCar Dataset}},
  Journal = {The International Journal of Robotics Research (IJRR)},
  Volume = {36},
  Number = {1},
  Pages = {3-15},
  Year = {2017},
  doi = {10.1177/0278364916679498},
  URL =
{http://dx.doi.org/10.1177/0278364916679498},
  eprint =
{http://ijr.sagepub.com/content/early/2016/11/28/0278364916679498.full.pdf+html},
  Pdf = {http://robotcar-dataset.robots.ox.ac.uk/images/robotcar_ijrr.pdf}}

License

SE3_Pose_Interp is released under a MIT license (see LICENSE.txt)

If you use SE3_Pose_Interp in an academic work, please cite the most relevant publication associated by visiting: https://rancheng.github.io

Owner
Ran Cheng
Robotics, Vision, Learning
Ran Cheng
Which Style Makes Me Attractive? Interpretable Control Discovery and Counterfactual Explanation on StyleGAN

Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN Which Style Makes Me Attractive? Interpretable Control Discovery an

Bo Li 11 Dec 01, 2022
CompilerGym is a library of easy to use and performant reinforcement learning environments for compiler tasks

CompilerGym is a library of easy to use and performant reinforcement learning environments for compiler tasks

Facebook Research 721 Jan 03, 2023
PyTorch code for Composing Partial Differential Equations with Physics-Aware Neural Networks

FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t

Cognitive Modeling 20 Dec 18, 2022
Sequential model-based optimization with a `scipy.optimize` interface

Scikit-Optimize Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements

Scikit-Optimize 2.5k Jan 04, 2023
Source code for our paper "Empathetic Response Generation with State Management"

Source code for our paper "Empathetic Response Generation with State Management" this repository is maintained by both Jun Gao and Yuhan Liu Model Ove

Yuhan Liu 3 Oct 08, 2022
WormMovementSimulation - 3D Simulation of Worm Body Movement with Neurons attached to its body

Generate 3D Locomotion Data This module is intended to create 2D video trajector

1 Aug 09, 2022
Implementation for Paper "Inverting Generative Adversarial Renderer for Face Reconstruction"

StyleGAR TODO: add arxiv link Implementation of Inverting Generative Adversarial Renderer for Face Reconstruction TODO: for test Currently, some model

155 Oct 27, 2022
Pytorch implementation of RED-SDS (NeurIPS 2021).

Recurrent Explicit Duration Switching Dynamical Systems (RED-SDS) This repository contains a reference implementation of RED-SDS, a non-linear state s

Abdul Fatir 10 Dec 02, 2022
A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

CLEVR Dataset Generation This is the code used to generate the CLEVR dataset as described in the paper: CLEVR: A Diagnostic Dataset for Compositional

Facebook Research 503 Jan 04, 2023
pytorch implementation of openpose including Hand and Body Pose Estimation.

pytorch-openpose pytorch implementation of openpose including Body and Hand Pose Estimation, and the pytorch model is directly converted from openpose

Hzzone 1.4k Jan 07, 2023
This is the code for Deformable Neural Radiance Fields, a.k.a. Nerfies.

Deformable Neural Radiance Fields This is the code for Deformable Neural Radiance Fields, a.k.a. Nerfies. Project Page Paper Video This codebase conta

Google 1k Jan 09, 2023
Implementation of paper: "Image Super-Resolution Using Dense Skip Connections" in PyTorch

SRDenseNet-pytorch Implementation of paper: "Image Super-Resolution Using Dense Skip Connections" in PyTorch (http://openaccess.thecvf.com/content_ICC

wxy 114 Nov 26, 2022
Code for ACM MM 2020 paper "NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination"

NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination The offical implementation for the "NOH-NMS: Improving Pedestrian Detection by

Tencent YouTu Research 64 Nov 11, 2022
GDR-Net: Geometry-Guided Direct Regression Network for Monocular 6D Object Pose Estimation. (CVPR 2021)

GDR-Net This repo provides the PyTorch implementation of the work: Gu Wang, Fabian Manhardt, Federico Tombari, Xiangyang Ji. GDR-Net: Geometry-Guided

169 Jan 07, 2023
Unsupervised Foreground Extraction via Deep Region Competition

Unsupervised Foreground Extraction via Deep Region Competition [Paper] [Code] The official code repository for NeurIPS 2021 paper "Unsupervised Foregr

28 Nov 06, 2022
Python code to generate art with Generative Adversarial Network

GAN_Canvas_Maker Generating Art using Generative Adversarial Network (GAN) Python code to generate art with Generative Adversarial Network: https://to

Jonny Banana 10 Aug 22, 2022
NAVER BoostCamp Final Project

CV 14조 final project Super Resolution and Deblur module Inference code & Pretrained weight Repo SwinIR Deblur 실행 방법 streamlit run WebServer/Server_SRD

JiSeong Kim 5 Sep 06, 2022
A library that allows for inference on probabilistic models

Bean Machine Overview Bean Machine is a probabilistic programming language for inference over statistical models written in the Python language using

Meta Research 234 Dec 29, 2022
中文语音识别系列,读者可以借助它快速训练属于自己的中文语音识别模型,或直接使用预训练模型测试效果。

MASR中文语音识别(pytorch版) 开箱即用 自行训练 使用与训练分离(增量训练) 识别率高 说明:因为每个人电脑机器不同,而且有些安装包安装起来比较麻烦,强烈建议直接用我编译好的docker环境跑 目前docker基础环境为ubuntu-cuda10.1-cudnn7-pytorch1.6.

发送小信号 180 Dec 17, 2022
2020 CCF大数据与计算智能大赛-非结构化商业文本信息中隐私信息识别-第7名方案

2020CCF-NER 2020 CCF大数据与计算智能大赛-非结构化商业文本信息中隐私信息识别-第7名方案 bert base + flat + crf + fgm + swa + pu learning策略 + clue数据集 = test1单模0.906 词向量

67 Oct 19, 2022