termed as 3D local convolutional neural networks. Our local operations can be combined with any existing architectures. We demonstrate the superiority of local operations on the task of gait ...

Abstract: The goal of gait recognition is to learn the unique spatiotemporal pattern about the human body shape from its temporal changing characteristics. As different body parts behave differently ...

It uses Keras with Tensorflow as backend. It uses CASIA-B Dataset to do subject subject\person classification using 3-D Convolution Networks on Gait Silhouette images obtained from the mentioned ...

Methods: To address this issue, we specifically designed a method combining 3D skeleton data and deep convolutional neural network (DCNN ... Existing Kinect-based methods are only designed for gait ...

Research harnessing the capabilities of deep learning frameworks to improve gait recognition methods has been geared to convolutional neural network (CNN) frameworks, which take into account ...