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

Jegoon Ryu, Sei Ichiro Kamata

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages3209-3212
Number of pages4
DOIs
Publication statusPublished - 2011 Dec 1
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 2011 Sep 112011 Sep 14

Publication series

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

Conference

Conference2011 18th IEEE International Conference on Image Processing, ICIP 2011
CountryBelgium
CityBrussels
Period11/9/1111/9/14

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

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  • Cite this

    Ryu, J., & Kamata, S. I. (2011). Front view gait recognition using spherical space model with human point clouds. In ICIP 2011: 2011 18th IEEE International Conference on Image Processing (pp. 3209-3212). [6116351] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2011.6116351