Detecting heel strikes for gait analysis through acceleration flow
In some forms of gait analysis, it is important to be able to capture when the heel strikes occur. In addition, in terms of video analysis of gait, it is important to be able to localise the heel where it strikes on the floor. In this study, a new motion descriptor, acceleration flow, is introduced...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-08-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2017.0429 |
| _version_ | 1797684810721787904 |
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| author | Yan Sun Jonathon S. Hare Mark S. Nixon |
| author_facet | Yan Sun Jonathon S. Hare Mark S. Nixon |
| author_sort | Yan Sun |
| collection | DOAJ |
| description | In some forms of gait analysis, it is important to be able to capture when the heel strikes occur. In addition, in terms of video analysis of gait, it is important to be able to localise the heel where it strikes on the floor. In this study, a new motion descriptor, acceleration flow, is introduced for detecting heel strikes. The key frame of heel strike can be determined by the quantity of acceleration flow within the region of interest, and positions of the strike can be found from the centre of rotation caused by radial acceleration. Our approach has been tested on a number of databases which were recorded indoors and outdoors with multiple views and walking directions for evaluating the detection rate under various environments. Experiments show the ability of our approach for both temporal detection and spatial positioning. The immunity of this new approach to three anticipated types of noises in real CCTV footage is also evaluated in our experiments. The authors acceleration flow detector is shown to be less sensitive to Gaussian white noise, whilst being effective with images of low‐resolution and with incomplete body position information when compared with other techniques. |
| first_indexed | 2024-03-12T00:35:11Z |
| format | Article |
| id | doaj.art-72802d563aa64d0ca3c0d497479ca910 |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:35:11Z |
| publishDate | 2018-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-72802d563aa64d0ca3c0d497479ca9102023-09-15T09:48:11ZengWileyIET Computer Vision1751-96321751-96402018-08-0112568669210.1049/iet-cvi.2017.0429Detecting heel strikes for gait analysis through acceleration flowYan Sun0Jonathon S. Hare1Mark S. Nixon2School of Electronics and Computer Science, University of SouthamptonSouthamptonUKSchool of Electronics and Computer Science, University of SouthamptonSouthamptonUKSchool of Electronics and Computer Science, University of SouthamptonSouthamptonUKIn some forms of gait analysis, it is important to be able to capture when the heel strikes occur. In addition, in terms of video analysis of gait, it is important to be able to localise the heel where it strikes on the floor. In this study, a new motion descriptor, acceleration flow, is introduced for detecting heel strikes. The key frame of heel strike can be determined by the quantity of acceleration flow within the region of interest, and positions of the strike can be found from the centre of rotation caused by radial acceleration. Our approach has been tested on a number of databases which were recorded indoors and outdoors with multiple views and walking directions for evaluating the detection rate under various environments. Experiments show the ability of our approach for both temporal detection and spatial positioning. The immunity of this new approach to three anticipated types of noises in real CCTV footage is also evaluated in our experiments. The authors acceleration flow detector is shown to be less sensitive to Gaussian white noise, whilst being effective with images of low‐resolution and with incomplete body position information when compared with other techniques.https://doi.org/10.1049/iet-cvi.2017.0429heel strikes detectiongait analysisacceleration flow quantitymotion descriptorkey frameregion-of-interest |
| spellingShingle | Yan Sun Jonathon S. Hare Mark S. Nixon Detecting heel strikes for gait analysis through acceleration flow IET Computer Vision heel strikes detection gait analysis acceleration flow quantity motion descriptor key frame region-of-interest |
| title | Detecting heel strikes for gait analysis through acceleration flow |
| title_full | Detecting heel strikes for gait analysis through acceleration flow |
| title_fullStr | Detecting heel strikes for gait analysis through acceleration flow |
| title_full_unstemmed | Detecting heel strikes for gait analysis through acceleration flow |
| title_short | Detecting heel strikes for gait analysis through acceleration flow |
| title_sort | detecting heel strikes for gait analysis through acceleration flow |
| topic | heel strikes detection gait analysis acceleration flow quantity motion descriptor key frame region-of-interest |
| url | https://doi.org/10.1049/iet-cvi.2017.0429 |
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