{"type":"ScholarlyArticle","title":"Human Action Recognition Using a Temporal Hierarchy of Covariance Descriptors on 3D Joint Locations","authors":[{"name":"Mohamed Elsayed Hussein","slug":"mohamed-elsayed-hussein","given":"Mohamed Elsayed","family":"Hussein","affiliation":""},{"name":"Marwan Torki","slug":"marwan-torki","given":"Marwan","family":"Torki","affiliation":""},{"name":"Mohammad Abdelaziz Gowayyed","slug":"mohammad-abdelaziz-gowayyed","given":"Mohammad Abdelaziz","family":"Gowayyed","affiliation":""},{"name":"Motaz El-Saban","slug":"motaz-el-saban","given":"Motaz","family":"El-Saban","affiliation":""}],"abstract":"Human action recognition from videos is a challenging machine vision task with multiple important application domains, such as human-robot/machine interaction, interactive entertainment, multimedia information retrieval, and surveillance. In this paper, we present a novel approach to human action recognition from 3D skeleton sequences extracted from depth data. We use the covariance matrix for skeleton joint locations over time as a discriminative descriptor for a sequence. To encode the relationship between joint movement and time, we deploy multiple covariance matrices over sub-sequences in a hierarchical fashion. The descriptor has a fixed length that is independent from the length of the described sequence. Our experiments show that using the covariance descriptor with an off-the-shelf classification algorithm outperforms the state of the art in action recognition on multiple datasets, captured either via a Kinect-type sensor or a sophisticated motion capture system. We also include an evaluation on a novel large dataset using our own annotation.","doi":null,"url":"https://ijcai.org/proceedings/2013/363","pdf":"https://ijcai.org/proceedings/2013/0363.pdf","markdown":"https://ijcai.org/proceedings/2013/363.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/363","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":363,"pages":{"first":2466,"last":2471},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}