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最新的对于提高步态识别率的特征表示,这篇文章详细的介绍了新的步态识别的特征表示方法，通过这种特征表示方法，我们可以在步态识别的时候更好的识别。提高了我们步态识别在很多负责场景中不能运用的弊端。改善了目前步态识别在研究上面的缺陷。(the paper presents a new gait representation called SEGI to perform gait recognition)
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下载文件列表
View Transformation Model Incorporating Quality Measures for Cross-View Gait Recognition.pdf
A Grassmannian Approach to Address View Change Problem in Gait Recognition.pdf
Accelerometer-Based Gait Recognition by Sparse Representation of Signature Points With Clusters.pdf
Cross-Speed Gait Recognition Using Speed-Invariant Gait Templates and Globality-Locality Preserving Projections.pdf
Frontal Gait Recognition From Incomplete Sequences Using RGB-D Camera.pdf
Multi-person gait recognition system based on Kinect.pdf
Kernel-Based Fuzzy Local Binary Pattern for Gait Recognition.pdf
Persistent homology-based gait recognition robust to upper body variations.pdf
View invariant gait recognition using only one uniform model.pdf
Learning robust features for gait recognition by Maximum Margin Criterion.pdf
A Grassmannian Approach to Address View Change Problem in Gait Recognition.pdf
Accelerometer-Based Gait Recognition by Sparse Representation of Signature Points With Clusters.pdf
Cross-Speed Gait Recognition Using Speed-Invariant Gait Templates and Globality-Locality Preserving Projections.pdf
Frontal Gait Recognition From Incomplete Sequences Using RGB-D Camera.pdf
Multi-person gait recognition system based on Kinect.pdf
Kernel-Based Fuzzy Local Binary Pattern for Gait Recognition.pdf
Persistent homology-based gait recognition robust to upper body variations.pdf
View invariant gait recognition using only one uniform model.pdf
Learning robust features for gait recognition by Maximum Margin Criterion.pdf