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Heel strike detection based on human walking movement for surveillance analysis

Heel strike detection based on human walking movement for surveillance analysis
Heel strike detection based on human walking movement for surveillance analysis
Heel strike detection is an important cue for human gait recognition and detection in visual surveillance since the heel strike position can be used to derive the gait periodicity, stride and step length. We propose a novel method for heel strike detection using a gait trajectory model, which is robust to occlusion, camera view, and low resolution. When a person walks, the movement of the head is conspicuous and sinusoidal. The highest point of the trajectory of the head occurs when the feet cross (stance) and the lowest point is when the gait stride is the largest (heel strike). Our gait trajectory model is constructed from trajectory data using non-linear optimisation. Then, the key frames in which the heel strikes take place are calculated. A Region Of Interest (ROI) is extracted using the silhouette image of the key frame as a filter. For candidate detection, Gradient Descent is applied to detect maxima which are considered to be the time of the heel strikes. For candidate verification, two filtering methods are used to reconstruct the 3D position of a heel strike using the given camera projection matrix. The contribution of this research is the first use of the gait trajectory in the heel strike position estimation process and we contend that it is a new approach for basic analysis in surveillance imagery.
heel strike detection, gait trajectory model, walking direction, gait
895-902
Jung, Sung Uk
7d4ceed9-1bc6-4740-a398-b81a670438ba
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Jung, Sung Uk
7d4ceed9-1bc6-4740-a398-b81a670438ba
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Jung, Sung Uk and Nixon, Mark S. (2013) Heel strike detection based on human walking movement for surveillance analysis. Pattern Recognition Letters, 34 (8), 895-902. (doi:10.1016/j.patrec.2012.08.007).

Record type: Article

Abstract

Heel strike detection is an important cue for human gait recognition and detection in visual surveillance since the heel strike position can be used to derive the gait periodicity, stride and step length. We propose a novel method for heel strike detection using a gait trajectory model, which is robust to occlusion, camera view, and low resolution. When a person walks, the movement of the head is conspicuous and sinusoidal. The highest point of the trajectory of the head occurs when the feet cross (stance) and the lowest point is when the gait stride is the largest (heel strike). Our gait trajectory model is constructed from trajectory data using non-linear optimisation. Then, the key frames in which the heel strikes take place are calculated. A Region Of Interest (ROI) is extracted using the silhouette image of the key frame as a filter. For candidate detection, Gradient Descent is applied to detect maxima which are considered to be the time of the heel strikes. For candidate verification, two filtering methods are used to reconstruct the 3D position of a heel strike using the given camera projection matrix. The contribution of this research is the first use of the gait trajectory in the heel strike position estimation process and we contend that it is a new approach for basic analysis in surveillance imagery.

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More information

e-pub ahead of print date: 2012
Published date: 1 June 2013
Keywords: heel strike detection, gait trajectory model, walking direction, gait
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 346059
URI: http://eprints.soton.ac.uk/id/eprint/346059
PURE UUID: 7f7bd3e6-9630-4839-b8d9-51ecd7cfa22f
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 14 Dec 2012 10:10
Last modified: 29 Aug 2019 00:56

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Contributors

Author: Sung Uk Jung
Author: Mark S. Nixon ORCID iD

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