README.md

person-detection-action-recognition-0006

Use Case and High-Level Description

This is an action detector for the Smart Classroom scenario. It is based on the RMNet backbone that includes depth-wise convolutions to reduce the amount of computations for the 3x3 convolution block. The first SSD head from 1/8 and 1/16 scale feature maps has four clustered prior boxes and outputs detected persons (two class detector). The second SSD-based head predicts actions of the detected persons. Possible actions: sitting, writing, raising hand, standing, turned around, lie on the desk.

Example

Specification

Metric	Value
Detector AP (internal test set 2)	90.70%
Accuracy (internal test set 2)	80.74%
Pose coverage	sitting, writing, raising_hand, standing,
	turned around, lie on the desk
Support of occluded pedestrians	YES
Occlusion coverage	<50%
Min pedestrian height	80 pixels (on 1080p)
GFlops	8.225
MParams	2.001
Source framework	TensorFlow*

Average Precision (AP) is defined as an area under the precision/recall curve.

Inputs

Image, name: input, shape: 1, 400, 680, 3 in the format B, H, W, C, where:

• B - batch size
• H - image height
• W - image width
• C - number of channels

Expected color order is BGR.

Outputs

The net outputs four branches:

1. name: ActionNet/out_detection_loc, shape: b, num_priors, 4 - Box coordinates in SSD format
2. name: ActionNet/out_detection_conf, shape: b, num_priors, 2 - Detection confidences
3. name: ActionNet/action_heads/out_head_1_anchor_1, shape: b, 50, 85, 6 - Action confidences
4. name: ActionNet/action_heads/out_head_2_anchor_1, shape: b, 25, 43, 6 - Action confidences
5. name: ActionNet/action_heads/out_head_2_anchor_2, shape: b, 25, 43, 6 - Action confidences
6. name: ActionNet/action_heads/out_head_2_anchor_3, shape: b, 25, 43, 6 - Action confidences
7. name: ActionNet/action_heads/out_head_2_anchor_4, shape: b, 25, 43, 6 - Action confidences

Where:

• b - batch size
• num_priors - number of priors in SSD format (equal to 50x85x1+25x43x4=8550)

Demo usage

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:

• Smart Classroom C++ Demo
• Smart Classroom C++ G-API Demo

Legal Information

[*] Other names and brands may be claimed as the property of others.