A framework for gait-based recognition using Kinect
A framework for gait-based recognition using Kinect
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DOI：
10.1016/j.patrec.2015.06.020
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发表时间：
2015-12-15
影响因子：
5.1
通讯作者：
Fotopoulos, Spiros
中科院分区：
文献类型：
--
作者：
Kastaniotis, Dimitris;Theodorakopoulos, Ilias;Fotopoulos, Spiros
步态分析在过去几年中获得了新的推动力。这主要是由于伴随着实时姿态估计算法的低成本深度相机的推出。在这项工作中，我们主要研究人类步态识别问题。特别地，我们提出了对最初为动作识别任务设计的框架的修改，并将其应用于步态识别。新方案使我们能够实现步态序列的复杂表示，从而有效地表达人类行走序列的动态特征。我们在一个公开可用的数据集上评估了建议模型的代表性，我们在验证任务上实现了高达93.29%的识别率，3.1%的EER和99.11%的性别识别率。(C) 2015 Elsevier B.V.版权所有
Gait analysis has gained new impetus over the past few years. This is mostly due to the launch of low cost depth cameras accompanied with real time pose estimation algorithms. In this work we focus on the problem of human gait recognition. In particular, we propose a modification of a framework originally designed for the task of action recognition and apply it to gait recognition. The new scheme allows us to achieve complex representations of gait sequences and thus express efficiently the dynamic characteristics of human walking sequences. The representational power of the suggested model is evaluated on a publicly available dataset where we achieved up to 93.29% identification rate, 3.1% EER on the verification task and 99.11% gender recognition rate. (C) 2015 Elsevier B.V. All rights reserved.