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Human-human Front-following (HHFF) dataset

dataset
posted on 2023-12-04, 04:32 authored by Haoyang JiangHaoyang Jiang, Michael BurkeMichael Burke, Elizabeth Croft

This dataset recorded a leader-predictor front-following task that simulates a person-following scenario in a simulated indoor intersection assembled using retractable barriers in a Vicon motion capture arena. The arena has a diameter of approximately 5.0m, and the junction size is a 1.6mx1.6m square in order to permit comfortable side-by-side walking. The scenario involves two human participants: the predictor A and the leader B. At the beginning of each trial, B is asked to secretly select one of the destinations from 1, 2 and 3. The predictor A is asked to actively stay in front of B and attempt to reach the unknown destination in advance of B. When each trial begins, B walks naturally towards the selected destination, generally treating A as an unknown pedestrian (i.e., keeping a comfortable distance, no direct communication, but still following general social norms such as adjusting speed to avoid collision). After entering the intersection, A can move freely, provided they do not interfere with B's progress. Direct communication channels such as speaking or hand signals are forbidden, forcing participants to communicate via more subtle motion cues. This `front-following' task involves significant levels of observation, prediction and collaboration, providing an interesting setting to analyse the use of social cues. Seven participant pairs (14 individuals aged 19 to 31, 3 females, 11 males) were recruited from the Monash University Clayton campus. Participants provided consent at the start of the experiment (Approved by the Monash University ethics committee. Project ID: 33090). The Vicon system provides a default frame rate of around 200Hz. Vicon markers on a cap and a belt are used to track A and B's head and hip pose, with the centre position and the head and hip orientation recorded for each participant.

The related work that is associated with this dataset can be found here: https://doi.org/10.1145/3610977.3634933

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