Comments (2)
Hi, Thanks for sharing. I have some questions regards the pose refinement step. In the paper, you claimed that it is based on ICP and you only use a smaller number of EIPs to reduce the computation cost. In my view, the reason why ICP can achieve highly accurate results is that it uses dense point cloud to build the correspondences, while the initial odometry got by RANSAC is estimated using sparse keypoint correspondences. So I am really confused about this step. How many EIPs you are using for ICP? And have you done some ablation studies on the number of EIPs vs. the error decrease?
Thank you for your time.
Hi! Thanks for your interest in my work and sorry for the part that confuses you. The ablation studies were not shown in the preprint version currently.
The basic solution of using feature-based frame to frame matching to get an initial odometry and using full point clouds of the keyframes to refine the initial odometry will be easy to be understood. In our work, the use of EIPs is to decrease the computation on the refinement.
EIPs are obtained in the spherical ring structured data by picking up valid pixels around the detected interest points (pixels). The parameter ℎ𝐸 is fixed while the number of EIPs various. Because:
- the valid pixels surrounding one interest point is not fixed;
- sometimes there are overlaps between neighboring areas of interest points.
I hope that explains well.
from cae-lo.
Thanks a lot. That makes sense.
from cae-lo.
Related Issues (14)
- Training ,Model and inference code HOT 2
- Demo data does not contain ground truth poses HOT 1
- GetKeyPtsAndPatchesFromKeyPts function cannot be found in RefinePoses.py HOT 1
- Prediction of LiDAR pointcloud odometry HOT 1
- PlanarPts from the keyPtsData is empty HOT 1
- Which data can be substituted for dirKeyPts3DFeatNet in PoseEstimation.py? HOT 1
- Why don't you provide trajectories results in your paper?
- How to plot 3d pointcloud feature matching like figure 6 in your paper? HOT 2
- About Interest points and features HOT 6
- A question about the detail when pre-process KITTI Velodyne data HOT 9
- package version HOT 1
- what is python version HOT 1
- Cannot find the correct installation package for PCLKeypoint HOT 4
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from cae-lo.