Human Point Cloud Data Segmentation based on Normal Vector Estimation using PCA-SVD Approaches for Elderly Activity Daily Living Detection

Nova Eka Budiyanta, Eko Mulyanto Yuniarno, Mauridhi Hery Purnomo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


The use of cameras to monitor the elderly daily living activities might cause inconvenience related to the privacy issues. Thus, another sensor namely LiDAR which generates point cloud data is used to support the monitoring process. This study is aimed at segmenting human and ground data from LiDAR point cloud to obtain human data. A segmentation process using a normal vector search approach for each point perpendicular to its plane using Principal Component Analysis (PCA) assisted by k-dimensional Tree Nearest Neighbor (kdTree-NN) Singular Value Decomposition (SVD) is proposed and successfully implemented. KITTI dataset containing of 54 frames in which a human is walking towards the LiDAR sensor as a scene scenario was used. The trend of the number of raw data points increased by 12.58%. Furthermore, the trend in the number of data points segmented representing human also increased by 233.13%. Meanwhile, the data points segmented representing ground decreased by 6.36%. This is because the closer human walking to LiDAR, the wider the blank spot behind the human object is. Consequently, data points representing human increased significantly, reducing the number of data points representing the ground. The point clouds which both represent the human and the ground were successfully segmented. Therefore, the point cloud representing human was successfully obtained to be used in further research.

Original languageEnglish
Title of host publicationTENCON 2021 - 2021 IEEE Region 10 Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781665495325
Publication statusPublished - 2021
Externally publishedYes
Event2021 IEEE Region 10 Conference, TENCON 2021 - Auckland, New Zealand
Duration: 7 Dec 202110 Dec 2021

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450


Conference2021 IEEE Region 10 Conference, TENCON 2021
Country/TerritoryNew Zealand


  • Human Point Cloud
  • Normal Vector Estimation
  • PCA
  • SVD
  • Segmentation


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