Real-Time Height Measurement for Moving Pedestrians

Wenju Zhou, Fulong Yao, Wei Feng and Haikuan Wang

Complexity, 2020, vol. 2020, 1-15

Abstract:

Height measurement for moving pedestrians is quite significant in many scenarios, such as pedestrian positioning, criminal suspect tracking, and virtual reality. Although some existing height measurement methods can detect the height of the static people, it is hard to measure height accurately for moving pedestrians. Considering the height fluctuations in dynamic situation, this paper proposes a real-time height measurement based on the Time-of-Flight (TOF) camera. Depth images in a continuous sequence are addressed to obtain the real-time height of the pedestrian with moving. Firstly, a normalization equation is presented to convert the depth image into the grey image for a lower time cost and better performance. Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. Thirdly, a segmentation algorithm based on the maximally stable extremal regions (MSERs) is introduced to extract the pedestrian head region. Then, a novel multilayer iterative average algorithm (MLIA) is developed for obtaining the height of dynamic pedestrians. Finally, Kalman filtering is used to improve the measurement accuracy by combining the current measurement and the height at the last moment. In addition, the VICON system is adopted as the ground truth to verify the proposed method, and the result shows that our method can accurately measure the real-time height of moving pedestrians.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/8503/2020/5708593.pdf (application/pdf)
http://downloads.hindawi.com/journals/8503/2020/5708593.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:5708593

DOI: 10.1155/2020/5708593

Access Statistics for this article

More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().