Abstract
This paper introduces a new approach for gait analysis based on the Gait Energy Image (GEI). The main idea is to segment the gait cycle into some biomechanical poses, and to compute a particular GEI for each pose. Pose-based GEIs can better represent body parts and dynamics descriptors with respect to the usually blurred depiction provided by a general GEI. Gait classification is carried out by fusing separated pose-based decisions. Experiments on human identification prove the benefits of this new approach when compared to the original GEI method.
Partially supported by projects CSD2007-00018 and CICYT TIN2009-14205-C04-04 from the Spanish Ministry of Innovation and Science, P1-1B2009-04 from Fundació Bancaixa and PREDOC/2008/04 grant from Universitat Jaume I. Portions of the research in this paper use the CASIA Gait Database collected by Institute of Automation, Chinese Academy of Sciences.
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Martín-Félez, R., Mollineda, R.A., Sánchez, J.S. (2011). Human Recognition Based on Gait Poses. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_43
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DOI: https://doi.org/10.1007/978-3-642-21257-4_43
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