Front view gait recognition using spherical space model with human point clouds

Jegoon Ryu; Sei Ichiro Kamata

doi:10.1109/ICIP.2011.6116351

Front view gait recognition using spherical space model with human point clouds

Jegoon Ryu^*, Sei Ichiro Kamata

^*Corresponding author for this work

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

16 Citations (Scopus)

Abstract

In this paper, we propose a novel gait recognition framework which is Spherical Space Model with Human Point Clouds (SSM-HPC). A new gait representation is also introduced, which is called Marching in Place (MIP) gait and preserves the spatiotemporal characteristics of individual gait manner. Various researches for gait recognition have used human silhouette images from moving picture. This research uses Three Dimensional (3D) point clouds data of human body obtained from stereo camera, which has the scale-invariant property. The framework is applied for frontal view gait recognition. This framework showed superior results for gait recognition rate than other gait recognition methods.

Original language	English
Title of host publication	ICIP 2011
Subtitle of host publication	2011 18th IEEE International Conference on Image Processing
Pages	3209-3212
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2011.6116351
Publication status	Published - 2011 Dec 1
Event	2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium Duration: 2011 Sept 11 → 2011 Sept 14

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
ISSN (Print)	1522-4880

Conference

Conference	2011 18th IEEE International Conference on Image Processing, ICIP 2011
Country/Territory	Belgium
City	Brussels
Period	11/9/11 → 11/9/14

Keywords

Gait Recognition
Human Point Clouds (HPC)
Marching in Place (MIP) Gait
Spherical Space Model (SSM)

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

Access to Document

10.1109/ICIP.2011.6116351

Cite this

Front view gait recognition using spherical space model with human point clouds. / Ryu, Jegoon; Kamata, Sei Ichiro.

ICIP 2011: 2011 18th IEEE International Conference on Image Processing. 2011. p. 3209-3212 6116351 (Proceedings - International Conference on Image Processing, ICIP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ryu, J & Kamata, SI 2011, Front view gait recognition using spherical space model with human point clouds. in ICIP 2011: 2011 18th IEEE International Conference on Image Processing., 6116351, Proceedings - International Conference on Image Processing, ICIP, pp. 3209-3212, 2011 18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, Belgium, 11/9/11. https://doi.org/10.1109/ICIP.2011.6116351

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abstract = "In this paper, we propose a novel gait recognition framework which is Spherical Space Model with Human Point Clouds (SSM-HPC). A new gait representation is also introduced, which is called Marching in Place (MIP) gait and preserves the spatiotemporal characteristics of individual gait manner. Various researches for gait recognition have used human silhouette images from moving picture. This research uses Three Dimensional (3D) point clouds data of human body obtained from stereo camera, which has the scale-invariant property. The framework is applied for frontal view gait recognition. This framework showed superior results for gait recognition rate than other gait recognition methods.",

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AB - In this paper, we propose a novel gait recognition framework which is Spherical Space Model with Human Point Clouds (SSM-HPC). A new gait representation is also introduced, which is called Marching in Place (MIP) gait and preserves the spatiotemporal characteristics of individual gait manner. Various researches for gait recognition have used human silhouette images from moving picture. This research uses Three Dimensional (3D) point clouds data of human body obtained from stereo camera, which has the scale-invariant property. The framework is applied for frontal view gait recognition. This framework showed superior results for gait recognition rate than other gait recognition methods.

KW - Gait Recognition

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KW - Marching in Place (MIP) Gait

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Front view gait recognition using spherical space model with human point clouds

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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