Figure 1.

System Overview. The proposed system has two sub-sections: 3D pose estimator from 2D video input (top), gait feature extractor and classifier, and time-series-based Recurrent Neural Network (RNN) classifier (bottom). (a) 2D input video, (b) 2D pose estimator, (c) extracted 2D joint points with skeletal data of human pose, (d) 3D pose estimator, (e) 3D joint points, (f) processed 3D joint points, (g) gait feature extractor, (h) gait feature sets, (i) classifier based on gait features, (j) classified individual, (k) RNN trainer using spatiotemporal joint data, (l) trained RN model, (m) classifier using the RNN model, and (n) identified individual.