This benchmark aims to provide tools to evaluate 3D Interest Point Detection Algorithms with respect to human generated ground truth.

Using a web-based subjective experiment, human subjects marked 3D interest points on a set of 3D models. The models were organized in two datasets: Dataset A and Dataset B. Dataset A consists of 24 models which were hand-marked by 23 human subjects. Dataset B is larger with 43 models, and it contains all the models in Dataset B. The number of human subjects who marked all the models in this larger set is 16.

This benchmark aims to provide tools to evaluate 3D Interest Point Detection Algorithms with respect to human generated ground truth. Please refer to the paper for more information about this benchmark: "Helin Dutagaci, Chun Pan Cheung, Afzal Godil: Evaluation of 3D interest point detection techniques via human-generated ground truth", The Visual Computer, 2012.Using a web-based subjective experiment, human subjects marked 3D interest points on a set of 3D models. The models were organized in two datasets: Dataset A and Dataset B.

Objective: The objective of this track is to evaluate the performance of 3D shape retrieval approaches on Generic 3D Dataset.

Introduction: With the increasing number of 3D models are created every day and stored in databases, effectively searching a 3D repository for 3D shapes which are similar to a given 3D query model has become an important area of research. Benchmarking allows researchers to evaluate the quality of the results of different 3D shape retrieval approaches.

The objective of this SHREC'12 track is to evaluate the performance of different sketch-based 3D model retrieval algorithms using both hand-drawn and standard line drawings sketch queries on a watertight 3D model dataset.

**** Note that this SRD is superseded by SRD 64 Version 4.0. ****The NIST Electron Elastic-Scattering Cross-Section Database provides values of differential elastic-scattering cross sections, total elastic-scattering cross sections, phase shifts, and transport cross sections in electron-atom scattering for elements with atomic numbers from 1 to 96 and for electron energies between 50 eV and 300 keV (in steps of 1 eV).

The Web Thermo Tables (WTT) are a collection of critically evaluated thermodynamic property data for pure compounds with a primary focus on organics. These data were generated through dynamic data analysis, as implemented in the NIST ThermoData Engine software package. Also included are some critically evaluated data from the historical TRC Thermodynamic Tables archive. The Lite Edition is a subset of the data for commonly-used pure compounds.

Note that this SRD supersedes SRD 64 Version 3.2. The NIST Electron Elastic-Scattering Cross-Section Database provides values of differential elastic-scattering cross sections, total elastic-scattering cross sections, phase shifts, and transport cross sections in electron-atom scattering for elements with atomic numbers from 1 to 96 and for electron energies between 50 eV and 300 keV (in steps of 1 eV).

This atlas presents observations of the infra-red (IR) spectrum of a low current Th-Ar hollow cathode lamp with the 2-m Fourier transform spectrometer (FTS) at NIST. These observations establish more than 2400 lines that are suitable for use as wavelength standards in the range 691 nm to 5804 nm.

The Elemental Data Index provides access to the holdings of NIST Physical Measurement Laboratory (PML) online data organized by element. It is intended to simplify the process of retrieving online scientific data for a specific element from various online databases, including atomic spectroscopy, atomic data, x-ray absorption, and nuclear data. For some of the databases, the data are immediately retrieved; for others, the retrieval form is provided with the element entered in the form, but additional options must be selected in order to retrieve the data.

The National Institute of Standards and Technology, as part of its report on the collapse of the World Trade Center, characterized many important steels recovered from the buildings to provide stress-strain models to analyze the impact, fires, and resulting collapse. Those tests represent a large additional data set that can be used for modeling the response of steel structures to fire.