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The document discusses a gait recognition technique that uses 3D skeleton information from a Kinect sensor to track skeleton points over time. It computes covariance matrices between the skeleton point trajectories to form gait models for training and testing data. Gait recognition is performed by finding the minimum dissimilarity between these models, achieving over 90% accuracy on a dataset of 20 subjects under fixed and moving camera scenarios.
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- 2. ICVGIP Skeleton Points 2012
- 3. ICVGIP Gait Recognition 2012
- 4. ICVGIP Gait Recognition 2012 • Uses 3D skeleton information obtained from Microsoft Kinect SDK. • Temporal tracking of skeleton points. • The covariance measure between these skeleton point trajectories are computed and the co-variance matrices form the gait model. • The gait is recognized by computing the minimum dissimilarity measure between the gait models of the training data and testing data. • Recognition accuracy of over 90% has been achieved for a data set consisting of fixed and moving camera scenarios of 20 subjects.
- 5. ICVGIP Results 2012