person-detection-0100

Use Case and High-Level Description

This is a person detector that is based on MobileNetV2 backbone with two SSD heads from 1/16 and 1/8 scale feature maps and clustered prior boxes for 256x256 resolution.

Example

person-detection-0100.png

Specification

Metric Value
AP 82.52% (internal test set)
Pose coverage Standing upright, parallel to image plane
Support of occluded persons YES
Occlusion coverage <50%
Min person height 100 pixels (on 1080p)
GFlops 0.786
MParams 1.817
Source framework PyTorch*

Average Precision (AP) is defined as an area under the precision/recall curve. Intersection over union threshold of 0.5 is used for matching.

Performance

Inputs

Name: input, shape: [1x3x256x256] - An input image in the format [BxCxHxW], where:

Expected color order is BGR.

Outputs

The net outputs blob with shape: [1, 1, N, 7], where N is the number of detected bounding boxes. Each detection has the format [image_id, label, conf, x_min, y_min, x_max, y_max], where:

Legal Information

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