From: Estimation of gait normality index based on point clouds through deep auto-encoder
Model | Training data | Data type | Classification error (leave-one-out) | ||
---|---|---|---|---|---|
 |  |  | Per-frame | Segment | Entire seq. |
HMM [21] | Normal only | Skeleton | – | 0.396 | 0.198 |
One-class SVM [5] | Normal only | Silhouette | 0.418 | 0.274 | 0.136 |
Binary SVM [5] | Normal + abnormal | Silhouette | 0.110 | 0.152 | 0.111 |
HMM [23] | Normal only | Depth map | – | 0.473 | 0.431 |
Cross-correlation [23] | Normal only | Silhouette | – | 0.321 | 0.097 |
HMM + cross-correlation [23] | Normal only | Silhouette + depth map | – | 0.319 | 0.083 |
(Our) Sigmoid | Normal only | Point cloud | 0.362 | 0.240 | 0.160 |
(Our) Sigmoid + dropout | Normal only | Point cloud | 0.363 | 0.241 | 0.148 |
(Our) Tanh | Normal only | Point cloud | 0.298 | 0.144 | 0.049 |
(Our) Tanh + dropout | Normal only | Point cloud | 0.301 | 0.168 | 0.074 |
(Our) Leaky ReLU | Normal only | Point cloud | 0.297 | 0.173 | 0.099 |
(Our) Leaky ReLU + dropout | Normal only | Point cloud | 0.311 | 0.185 | 0.123 |
(Our) Multi-network | Normal only | Point cloud | 0.303 | 0.178 | 0.086 |