Abstract
In the present scenario, Gait descriptors are required to extract the dynamic and static information of the gait. The static and dynamic descriptors are formed from the entire region of the body. We know that majority of dynamic information is in the lower silhouette whereas majority of static information is in the upper silhouette. In our work we have evaluated the significance of dynamic information extracted from the lower silhouette. State of the art feature descriptors are used along with a feature selection mask to form the final signature templates for classification. Our results indicate a significant dynamic content in the lower silhouette which itself is able to give decent recognition rate. Future work can improve performance by using dynamic information from lower silhouette in conjunction with static information derived from upper silhouette.
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Saxena, S. (2011). Significance of Dynamic Content of Gait Present in the Lower Silhouette Region. In: Sun, Z., Lai, J., Chen, X., Tan, T. (eds) Biometric Recognition. CCBR 2011. Lecture Notes in Computer Science, vol 7098. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25449-9_20
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DOI: https://doi.org/10.1007/978-3-642-25449-9_20
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