Individual recognition using gait energy image

University of California, Riverside

PubMed
Indexed incrossrefpubmed

Abstract

In this paper, we propose a new spatio-temporal gait representation, called Gait Energy Image (GEI), to characterize human walking properties for individual recognition by gait. To address the problem of the lack of training templates, we also propose a novel approach for human recognition by combining statistical gait features from real and synthetic templates. We directly compute the real templates from training silhouette sequences, while we generate the synthetic templates from training sequences by simulating silhouette distortion. We use a statistical approach for learning effective features from real and synthetic templates. We compare the proposed GEI-based gait recognition approach with other gait…

Citation impact

1,849
total citations
FWCI
33.74
Percentile
100%
References
28
Citations per year

Authors

2

Topics & keywords

Keywords
  • Silhouette
  • Gait
  • Artificial intelligence
  • Computer science
  • Pattern recognition (psychology)
  • Representation (politics)
  • Computer vision
  • Template
UN Sustainable Development Goals
  • Affordable and clean energy
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