Triangle and Trapezoid Area Features for Gait Authentication

Abstract

This paper presents two gait authentication features based on geometric shape for gait analysis. Specifically, triangle and trapezoid based features are proposed for gait authentication. The features are based on the geometric pattern extracted from a particular gait cycle of a gait model. These features use four points from hip-knee-toe joints and construct a triangle and a right trapezoid. The area of the triangle and trapezoid are calculated using geometric formula as well as image processing methods. Later two areas are compared to validate the model free approach. The results show that, the proposed feature can be used as the features in model free gait analysis.

Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification

“…Notably, any sequential spatiotemporal gait data can also be estimated from a single-camera-based marker-less 2D video system employing lateral-view video of a walking individual because continuous 2D image sequences from the video can show the continuous body postures of human gait [ 21 , 22 ]. This 2D approach is currently gaining popularity as an alternative to the marker-based optoelectronic system due to its simplicity, rapidity, and ability to potentially provide more significant assessments of human movement in research and clinical practice [ 23 , 24 , 25 , 26 ].…”