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Estimation of 3D Head Region using Gait Motion for Surveillance Video

Estimation of 3D Head Region using Gait Motion for Surveillance Video
Estimation of 3D Head Region using Gait Motion for Surveillance Video
Detecting and recognizing people is important in surveillance. Many detection approaches use local information, such as pattern and colour, which can lead to constraints on application such as changes in illumination, low resolution, and camera view point. In this paper we propose a novel method for estimating the 3D head region based on analysing the gait motion derived from the video provided by a single camera. Generally, when a person walks there is known head movement in the vertical direction, regardless of the walking direction. Using this characteristic the gait period is detected using wavelet decomposition and the heel strike position is calculated in 3D space. Then, a 3D gait trajectory model is constructed by non-linear optimization. We evaluate our new approach using the CAVIAR database and show that we can indeed determine the head region to good effect. The contributions of this research include the first use of detecting a face region by using human gait and which has fewer application constraints than many previous approaches.
3D Head position, gait period detection, heel strike detection, walking direction, gait
Jung, Sung Uk
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Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Jung, Sung Uk
7d4ceed9-1bc6-4740-a398-b81a670438ba
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Jung, Sung Uk and Nixon, Mark (2011) Estimation of 3D Head Region using Gait Motion for Surveillance Video. International Conference on Imaging for Crime Detection and Prevention, Kingston, United Kingdom. 03 - 04 Nov 2011.

Record type: Conference or Workshop Item (Poster)

Abstract

Detecting and recognizing people is important in surveillance. Many detection approaches use local information, such as pattern and colour, which can lead to constraints on application such as changes in illumination, low resolution, and camera view point. In this paper we propose a novel method for estimating the 3D head region based on analysing the gait motion derived from the video provided by a single camera. Generally, when a person walks there is known head movement in the vertical direction, regardless of the walking direction. Using this characteristic the gait period is detected using wavelet decomposition and the heel strike position is calculated in 3D space. Then, a 3D gait trajectory model is constructed by non-linear optimization. We evaluate our new approach using the CAVIAR database and show that we can indeed determine the head region to good effect. The contributions of this research include the first use of detecting a face region by using human gait and which has fewer application constraints than many previous approaches.

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More information

Published date: 3 November 2011
Additional Information: Event Dates: 3-4 November 2011
Venue - Dates: International Conference on Imaging for Crime Detection and Prevention, Kingston, United Kingdom, 2011-11-03 - 2011-11-04
Keywords: 3D Head position, gait period detection, heel strike detection, walking direction, gait
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 273217
URI: http://eprints.soton.ac.uk/id/eprint/273217
PURE UUID: dc578236-7279-4609-bc76-89f803e35407
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 17 Feb 2012 14:27
Last modified: 15 Mar 2024 02:35

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Contributors

Author: Sung Uk Jung
Author: Mark Nixon ORCID iD

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