head-pose-estimation-adas-0001¶
Use Case and High-Level Description¶
Head pose estimation network based on simple, handmade CNN architecture. Angle regression layers are convolutions + ReLU + batch norm + fully connected with one output.
Validation Dataset¶
Example¶
![_images/head-pose-estimation-adas-0001.png](_images/head-pose-estimation-adas-0001.png)
Specification¶
Metric |
Value |
---|---|
Supported ranges |
YAW [-90,90], PITCH [-70,70], ROLL [-70,70] |
GFlops |
0.105 |
MParams |
1.911 |
Source framework |
Caffe* |
Accuracy¶
Angle |
Mean ± standard deviation of absolute error |
---|---|
yaw |
5.4 ± 4.4 |
pitch |
5.5 ± 5.3 |
roll |
4.6 ± 5.6 |
Inputs¶
Image, name: data
, shape: 1, 3, 60, 60
in 1, C, H, W
format, where:
C
- number of channelsH
- image heightW
- image width
Expected color order is BGR
.
Outputs¶
Each output contains one float value that represents value in Tait-Bryan angles (yaw, pitch or roll).
name:
angle_y_fc
, shape:1, 1
- Estimated yaw (in degrees).name:
angle_p_fc
, shape:1, 1
- Estimated pitch (in degrees).name:
angle_r_fc
, shape:1, 1
- Estimated roll (in degrees).
Legal Information¶
[*] Other names and brands may be claimed as the property of others.