Computers & Graphics

# PinMesh PinMesh is an exact and efficient parallel algorithm for preprocess a polyhedral triangular mesh and, then, query a cloud of points against the mesh. PinMesh is described in the following paper: Magalhães SVG, et al. PinMesh - Fast and exact 3D point location queries using a uniform grid. Comput Graph (2016), http://www.sciencedirect.com/science/article/pii/S0097849316300607

Extrinsic - Zhiyang Huang (2016) ------------------------------------ This code implements the algorithm described in Huang Z, Ju T. Extrinsically smooth direction fields. Comput Graph(2016), http://dx.doi.org/10.1016/j.cag.2016.05.015i The basic function of this program is to compute extrinsically smooth direction fields “g” upon a curve, surface or volume while giving a references field “f”, such that “g” is orthogonal to “f”. In particular, the default setting of “f” for curve and surface are tangent field of the curve and normal field of the surface, respectively. The parameter-free initialization method based on least eigenvector problem and the Gauss–Seidel iterations, as described in the above paper, are implemented in this code and subjected to use. Currently the code is only tested on Mac OS X 10.10 or above, it should work at other platforms with minor modification.

# The 2D shape structure dataset: A user annotated open access database #### A Carlier, K Leonard, S Hahmann, G Morin, M Collins This code was tested on Matlab R2015a, on Ubuntu 14.04 and on Mac OS 10.9.5.

Running code produced for the paper Computing a Discrete Morse Gradient From a Watershed Decomposition Lidija Comic, Leila De Floriani, Federico Iuricich, Paola Magillo Tested Operating Sytem MacOSX 10.11.4

This CSV provides the corresponding RGB values for a specific color temperature (measured in Kelvin). It can be used to determine the appropriate RGB color values for a given color temperature. This dataset provides an approximation following the CIE 1964 colour-matching functions that is intended for low to mid quality output media (such as LED lighting, consumer screens and consumer grade VR headsets).

You may find the most recent version of the source code on GitHub: https://github.com/MunzT/NMTVis Trained models for translation from German to English and vice versa can be found here: https://doi.org/10.18419/darus-1850

We provide a database aimed at real-time quantitative analysis of 3D reconstruction and alignment methods, containing 3140 point clouds from 10 scenes. These scenes are acquired with a high-resolution 3D scanner. It contains depth maps that produce point clouds with more than 500k points on average.
This dataset is useful to develop new models and alignment strategies to automatically reconstruct 3D scenes from data acquired with optical scanners or benchmarking purposes with respect to state-of-the-art methods.

The dataset contains two type of files:
- ".npz" files are python readable files containing the point clouds and additional metadata to use.
- ".tar.gz" is a single large zip file which contains the different folders labeled similarly to the pointclouds. Each folder contains the RGB-D images and the camera calibration parameters that were used to reconstruct the 3D data. These are also the original output produced by the 3D scanner used to generate the data.
A Python reader for those files is also provided in the project repository which is linked in the notes.

This research project was undertaken as part of work was supported by the UK’s Engineering and Physical Sciences Research Council [EP/K008196/1]. Sixteen undergraduate students performed sketching tasks using “Gravity Sketch 3D” (GSVR) and the HTC Vive VR system in a physical area of 2.5 by 2 metres. All VR sketches were screen recorded using a VR-capable laptop computer. A wide-angle video camera was used to record the participants’ physical actions as they moved around the room. Another video camera was positioned directly above a drawing board to capture the production of paper-based sketches. To record the participants’ utterances during the study, they wore a lapel microphone connected wirelessly to a radio receiver unit connected to the laptop. To facilitate review and analysis, the video recordings from the VR sketching sessions were edited to produce synchronized picture-in-picture videos showing the participants’ physical actions and the images they were producing with those actions (e.g. 3D sketches in VR).

Version that contains all details to setup the Massive PointClouds benchmark.