dc.contributor.author | Yuan, Fuqing | |
dc.contributor.author | Lu, Jinmei | |
dc.date.accessioned | 2022-01-05T08:18:23Z | |
dc.date.available | 2022-01-05T08:18:23Z | |
dc.date.issued | 2021-03-16 | |
dc.description.abstract | Motion detection is vital for consumer electronics and the Internet of things (IOT).
For a scenario where the motion is slow and gentle, the resolution of the motion sensor is critical
for the detection, while the algorithm development is another critical issue to differentiate the
motion signal from noise measurement. This paper investigates the feasibility of using higher
order statistics kurtosis as a motion indicator. Statistical hypothesis test has been developed to
assess the motion presence. Several experiments are conducted to test the feasibility and
performance of the approach. The results show the approach is feasible, but with some
limitations. | en_US |
dc.identifier.citation | Yuan F, Lu J. An Slow Motion Detection Algorithm using High Order Statistic Approach. Journal of Physics: Conference Series (JPCS). 2021;2009 | en_US |
dc.identifier.cristinID | FRIDAID 1928551 | |
dc.identifier.doi | 10.1088/1742-6596/1827/1/012152 | |
dc.identifier.issn | 1742-6588 | |
dc.identifier.issn | 1742-6596 | |
dc.identifier.uri | https://hdl.handle.net/10037/23593 | |
dc.language.iso | eng | en_US |
dc.publisher | IOP Publishing | en_US |
dc.relation.journal | Journal of Physics: Conference Series (JPCS) | |
dc.rights.accessRights | openAccess | en_US |
dc.rights.holder | Copyright 2022 IOP Publishing | en_US |
dc.subject | VDP::Technology: 500 | en_US |
dc.subject | VDP::Teknologi: 500 | en_US |
dc.title | An Slow Motion Detection Algorithm using High Order Statistic Approach | en_US |
dc.type.version | publishedVersion | en_US |
dc.type | Journal article | en_US |
dc.type | Tidsskriftartikkel | en_US |
dc.type | Peer reviewed | en_US |