Cyclostationary Processes on Shape Spaces for Gait-Based Recognition
Cyclostationary Processes on Shape Spaces for Gait-Based Recognition
复制标题
基于步态识别的形状空间循环平稳过程
DOI：
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复制
发表时间：
2006
期刊：
影响因子：
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通讯作者：
Anuj Srivastava
中科院分区：
文献类型：
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作者：
David Kaziska;Anuj Srivastava
我们提出了一种新的步态识别方法，认为步态序列的循环平稳过程的形状空间上的简单封闭曲线。因此，步态分析减少到量化这些随机过程的统计数据之间的差异。拟议办法的主要步骤是：（i）从IR视频数据中离线提取人体轮廓，（ii）使用分段测地线路径，连接观察到的形状，以在它们之间平滑插值，（iii）计算类内的平均步态周期，（即与人相关联），（iv）使用线性和非线性时间缩放的平均周期的配准，（iv）使用测地长度比较相应登记形状之间的平均周期。我们说明这种方法涉及26个主题的红外视频剪辑。
We present a novel approach to gait recognition that considers gait sequences as cyclostationary processes on a shape space of simple closed curves. Consequently, gait analysis reduces to quantifying differences between statistics underlying these stochastic processes. The main steps in the proposed approach are: (i) off-line extraction of human silhouettes from IR video data, (ii) use of piecewise-geodesic paths, connecting the observed shapes, to smoothly interpolate between them, (iii) computation of an average gait cycle within class (i.e. associated with a person) using average shapes, (iv) registration of average cycles using linear and nonlinear time scaling, (iv) comparisons of average cycles using geodesic lengths between the corresponding registered shapes. We illustrate this approach on infrared video clips involving 26 subjects.
DOI：
10.1109/tpami.2005.39
发表时间：
2005-02-01
影响因子：
23.6
作者：
Sarkar, S;Phillips, PJ;Bowyer, KW
通讯作者：
Bowyer, KW