Omkar2118/datasets huggingface dataset:
Vid2RealHRI online video and results dataset
Full name: Community embedded robotics: Vid2RealHRI online video and perceived social intelligence in human-robot encounters dataset

## Introduction
This dataset was gathered during the [Vid2RealHRI](https://vid2real.github.io/vid2realHRI/) study of humans’ perception of robots' intelligence in the context of an incidental Human-Robot encounter. The dataset contains participants' questionnaire responses to four video study conditions, namely Baseline, Verbal, Body language, and Body language + Verbal. The videos depict a scenario where a pedestrian incidentally encounters a quadruped robot trying to enter a building. The robot uses verbal commands or body language to try to ask for help from the pedestrian in different study conditions. The differences in the conditions were manipulated using the robot’s verbal and expressive movement functionalities.

## Dataset Purpose
The dataset includes the responses of human subjects about the robots' social intelligence used to validate the hypothesis that robot social intelligence is positively correlated with human compliance in an incidental human-robot encounter context. The video based dataset was also developed to obtain empirical evidence that can be used to design future real-world HRI studies.

## Dataset Contents
* Four videos, each corresponding to a study condition.
* Four sets of Perceived Social Intelligence Scale data. Each set corresponds to one study condition
* Four sets of compliance likelihood questions, each set include one Likert question and one free-form question
* One set of Godspeed questionnaire data.
* One set of Anthropomorphism questionnaire data.
* A csv file containing the participants demographic data, Likert scale data, and text responses.
* A data dictionary explaining the meaning of each of the fields in the csv file.

**More details and access to this data are available from the [Texas Data Repository](https://dataverse.tdl.org/dataset.xhtml?persistentId=doi:10.18738/T8/KAHJIB). **

This research is part of the [Vid2Real](https://vid2real.github.io/) project, supported by NSF Award #2219236 and [Good Systems](https://bridgingbarriers.utexas.edu/good-systems), a Grand Research Challenge at the University of Texas at Austin.

Introducing paper: Vid2Real HRI: Align video-based HRI study designs with real-world settings