Appearance changes due to viewing angle changes cause difficulties for most of the gait recognition methods. In this paper, we propose a new approach for multi-view recognition, which allows to recognize people walking on ...

The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on ...

Gait as biometrics has been widely used for human identi cation. However, direction changes cause di culties for most of the gait recognition systems, due to appearance changes. This study presents an e cient multi-view ...

In this paper, we introduce a new multi-view dataset for gait recognition. The dataset was recorded in an indoor scenario, using six convergent cameras setup to produce multi-view videos, where each video depicts a ...

Direction changes cause di culties for most of the gait recognition systems, due to appearance changes. We propose a new approach for multi-view gait recognition, which focuses on recognizing people walking on unconstrained ...

The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on ...

This work targets people identification in video based on the way they walk (i.e. gait). While classical methods typically derive gait signatures from sequences of binary silhouettes, in this work we explore the use of ...