I need to visualize a set of hairstyles in 3D using open3d (or any similar package, if that makes things easier). In particular, I am looking for a way to visualize one of the hairstyles of the USC-HairSalon dataset available here.
Each hairstyle consists of 10.000 hair strands, with each strand made of 100 points. In Blender, hairstyles can be represented in 3D using the script available here.
Do you have any suggestions on what could be an efficient way to represent all hair strands? Each dataset is stored in a .data file and needs to be processed before being rendered.
To load the reference head, I am using a few lines of code:
import open3d as o3d
mesh = o3d.io.read_triangle_mesh("./USC-HairSalon_dataset/Raw_data/head_model.obj")
mesh.compute_vertex_normals()
o3d.visualization.draw_geometries([mesh])
I have a network of polylines and point data that I am trying to split out into individual line segments based on a given starting point of the network. I know that this can be done using the ArcGIS network analyst extension but I am trying to use open source software. I think this can be done using Shapely Linear Referencing methods but I'm unsure. Any help would be greatly appreciated! I've included a diagram below of what I'm talking about.
I am looking for an algorithm for convert 3D Point Cloud to Depth Image in Python, especially 3D Face Point Cloud. Can you suggest me some tools or algorithms?
Thanks in advance.
I am using win10, python and c#. I want to calculate circumference of human parts (belly, biceps etc) with using point cloud or 3d scans like .stl .obj .ply. Now I can get the point cloud of human body with kinect v2. I have point cloud of human body, scanned 3d human body in .stl .obj .ply formats.
I need some ideas and infos about it. I don't know how to analyse the things I have and how to calculate what I want.
Here I found an example of what I am trying to do but It doesn't need to be perfectly stable like that, Its for a school homework. Maybe you can give me some ideas about how to achieve my goal. Thank you for your help.
https://www.youtube.com/watch?time_continue=48&v=jOvaZGloNRo
I get 3d scanned object with kinect v2 and use PCL to convert it into point cloud.
I don't know about using PCL with Python or C#. In general you are looking at the following steps:
Filtering the points to the interested region
Segmenting the shape
Extracting the parameters
If you're interested in only Python, then OpenCV might be the best option. You can also develop the core logic in C++ and wrap it for Python or C#. C++ also has some nice UI libaries (Qt, nanogui), please see the following details for achieving the objective with PCL
Filtering
CropBox or PassThrough can be used for this. It'll result in similar results as shown in the image assuming that the frame has been chosen properly. If not, the points cloud can be easily transformed
Segmenting the shape
Assuming you want an average circumference, you might need to experiment with Circle 2D, Circle 3D and Cylinder models. More details regarding usage and API are here. The method chosen can be simple SAC (Sample Consensus) like RANSAC (Random SAC) or advanced method like LMEDS (Least Median of Squares) or MLESAC (Max Likelihood Estimation SAC)
Extracting the parameters
All models have a radius field which can be used to find the circumference using standard formula (2*pi*r)
Disclaimer: Please take note that the shape is circular, not ellipse and the cylinder are right angled cylinders. So if the object measured (arm, or bicep) is not circular, the computed value might not be close to ground truth in extreme cases
I want to make a 3d point cloud from 3d modeling file(dae, obj...) using python code.
like http://upload.wikimedia.org/wikipedia/commons/4/4c/Point_cloud_torus.gif
I have no idea where to begin. Do I need polygon or mesh data or something?
If there were any algorithm for this let me help.
I saw many questions about create mesh from point cloud but it`s very hard to find about this topic.
thanks.