All Videos Tagged Human (Grasshopper) - Grasshopper

Octopus E + Human + Ladybug Window ptimization workflow

2017-02-09T13:04:58.030Z

Ive done plenty of further work since this video with added functionality and also improvements with the aim of being able to make graphs that look good enough so that I don't have to use Excel for data exports.

Part of thesis: Multi-objective Optimization of Fenestration Design in Residential spaces. The Case of MKB Greenhouse, Malmö, Sweden https://lup.lub.lu.se/st...

3_Color based segmentation_Sfm Point Cloud_Volvox for Grasshopper_HumanUI.

2016-11-17T21:24:53.407Z

Edit and analysis of SfM point clouds in Grasshopper for Rhino. Primarily using Volvox and HumanUI plugins. Dense 3d point clouds are reconstructed from photo-sets in Agisoft Photoscan.

The video demonstrates the following:
1. The definition's functionality employing HumanUI for the custom user interface.
2. Color based segmentation in manual and auto modes.
3. The evaluation of the definition's ability to handle different point cloud data sets.

This definition performs color based segmentation in two modes.
A manual mode, that implements the Delta-E CIE 2000 color difference formula, for targeted feature detection. An auto mode, that employs a simple RGB Color Range algorithm for quicker preliminary results.

RGB to XYZ to CIELab conversion and Delta-E scripts were based on Colormine's project code from github. Results have been compared and verified with the results of http://colormine.org/color-converter and http://colormine.org/delta-e-calculator/Cie2000.

Each stored class is charted and can be accessed through the UI, as shown at 2:30, where Delta-E CIE 2000, in CieLab color space, output results were found to be in perceptive conformity with human eyes, far superior to the preliminary RGB implementation.

Initial definition versions could process highly subsampled clouds in acceptable timings. Further research showed that employing the multithread processing of Volvox components, bundling the Delta E formula with the RGB to CIE lab color conversion script, per color segmentation calculations for a one million points point cloud would go down from 23 (c# script component) and 8 (vb script component) seconds to approx. 1 second (volvox script cloud component), thus allowing the segmentation of less subsampled point clouds.

I would like to thank Heumann A. and Zwierzycki M. who provided direct support with HumanUI and Volvox. Also Grasshopper3d forum users Maher S. and Segeren P., who contributed with Rhino viewport manipulation scripts.

More on Volvox:
http://papers.cumincad.org/cgi-bin/works/Show?_id=ecaade2016_171&sort=DEFAULT&search=ecaade%20volvox&hits=2629
http://www.food4rhino.com/app/volvox
http://duraark.eu/

HumanUI:
http://www.food4rhino.com/app/human-ui?page=1&ufh=&etx=

ColorMine:
https://github.com/THEjoezack/ColorMine

2_Best fitting plane deviation_Sfm Point Cloud_Volvox for Grasshopper_HumanUI.

2016-11-17T21:22:42.948Z

Edit and analysis of SfM point clouds in Grasshopper for Rhino. Primarily using Volvox and HumanUI plugins. Dense 3d point clouds are reconstructed from photo-sets in Agisoft Photoscan.

The video demonstrates the following:
1. The definition's functionality employing HumanUI for the custom user interface.
2. The evaluation of the definition's ability to handle different point cloud data sets.
3. Video reports with the definition's results, animating subsequent per deviation step frames.

This definition calculates best fitting plane deviations. The number of manual set parameters has been minimized to two the facade per World UCS axis selection and the search width. This defines a box, which is used to crop protruding architectural details, which do not contribute to the analysis, but also ensures that large deformations are included in the calculation.

For the automation of the vertical and horizontal sections creation, the analyzed cloud is clustered, according to user defined number of 2d grid cells. The deviations corresponding to each cell are averaged in mean and median mode.

The process is displayed mostly in real time, with some speed up in some parts. Too long calculations have been omitted during video edit. The setup is responsive and benchmarks show that changing between dense point cloud data sets and facades is pretty quick (6.5-7.5M points, 25-45 deviation steps, 44x22 clusters), updates are calculated in acceptable timings (3-6 minutes).

I would like to thank Heumann A. and Zwierzycki M. who provided direct support with HumanUI and Volvox. Also Grasshopper3d forum users Maher S. and Segeren P., who contributed with Rhino viewport manipulation scripts.

More on Volvox:
http://papers.cumincad.org/cgi-bin/works/Show?_id=ecaade2016_171&sort=DEFAULT&search=ecaade%20volvox&hits=2629
http://www.food4rhino.com/app/volvox
http://duraark.eu/

HumanUI:
http://www.food4rhino.com/app/human-ui?page=1&ufh=&etx=

1_Orient_scale_Sfm Point Cloud_Volvox for Grasshopper_HumanUI.

2016-11-17T21:19:59.894Z

Pinecone project (KUKUNARI origins)

2016-07-07T12:22:31.823Z

Wrapping up and creating some demo presentations of the final projects of TUC ARCH230 postgraduate course

In this case Pinecone project by Iro Skouloudi was edited/adapted to Human UI for demonstration purposes.

This is the first stage of the given brief, where students had at first to learn the basics of grasshopper for Rhino (first time exposed to GH for most of them) and then move forward to the creation of a light fixture, which would be 3d printed at a small scale.

This project, after the course has been developed to KUKUNARI.