A portable three-dimensional LIDAR-based system for long-term and wide-area people behavior measurement

By Kenji Koide, Jun Miura, Emanuele Menegatti. International Journal of Advanced Robotic Systems, 2019

394 citations recorded by the source corpus.

It is important to measure and analyze people behavior to design systems which interact with people. This article describes a portable people behavior measurement system using a three-dimensional LIDAR. In this system, an observer carries the system equipped with a three-dimensional Light Detection and Ranging (LIDAR) and follows persons to be measured while keeping them in the sensor view. The system estimates the sensor pose in a three-dimensional environmental map and tracks the target persons. It enables long-term and wide-area people behavior measurements which are hard for existing people tracking systems. As a field test, we recorded the behavior of professional caregivers attending elderly persons with dementia in a hospital. The preliminary analysis of the behavior reveals how the caregivers decide the attending position while checking the surrounding people and environment. Based on the analysis result, empirical rules to design the behavior of attendant robots are proposed.

Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/943b49c98e86ca56caa77d46cf4cbe2e251aad90

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Lihua Xie

In Computer Vision and Pattern Recognition

1. Chen Wang
2. Lihua Xie
3. César Debeunne
4. Han Wang
5. Chun-Lin Chen
6. Damien Vivet

Citations in the corpus

• A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping (2020, background): “Note that edges e ij model the proprioceptive information constraint and Ω ij the exteroceptive one.”
• F-LOAM : Fast LiDAR Odometry and Mapping (2021, methodology): “with the open-sourced state-of-the-art LiDAR methods such as LOAM [10], A-LOAM, HDL-Graph-SLAM [28], IMLSSLAM [9], and LeGO-LOAM [11].”