From: Estimation of gait normality index based on point clouds through deep auto-encoder
Model | Training data | Data type | Classification error (4 test subjects) †| ||
---|---|---|---|---|---|
 |  |  | Per-frame | Segment | Entire seq. |
HMM [21] | Normal only | Skeleton | - | 0.335 | 0.250 |
One-class SVM [5] | Normal only | Silhouette | 0.399 | 0.227 | 0.139 |
Binary SVM [5] | Normal + abnormal | Silhouette | 0.104 | 0.157 | 0.139 |
HMM [23] | Normal only | Depth map | - | 0.396 | 0.281 |
Cross-correlation [23] | Normal only | Silhouette | - | 0.381 | 0.250 |
HMM + cross-correlation [23] | Normal only | Silhouette + depth map | - | 0.377 | 0.218 |
(Our) Sigmoid | Normal only | Point cloud | 0.332 | 0.264 | 0.250 |
(Our) Sigmoid + dropout | Normal only | Point cloud | 0.328 | 0.261 | 0.250 |
(Our) Tanh | Normal only | Point cloud | 0.298 | 0.158 | 0.111 |
(Our) Tanh + dropout | Normal only | Point cloud | 0.289 | 0.136 | 0.111 |
(Our) Leaky ReLU | Normal only | Point cloud | 0.326 | 0.125 | 0.028 |
(Our) Leaky ReLU + dropout | Normal only | Point cloud | 0.296 | 0.103 | 0.028 |
(Our) Multi-network | Normal only | Point cloud | 0.288 | 0.125 | 0.083 |