The keypoint detection part in PaddleDetection follows the state-of-the-art algorithm closely, including Top-Down and Bottom-Up methods, which can satisfy the different needs of users.
The keypoint detection part in PaddleDetection follows the state-of-the-art algorithm closely, including Top-Down and Bottom-Up methods, which can satisfy the different needs of users.
Top-Down detects the object first and then detect the specific keypoint. The accuracy of Top-Down models will be higher, but the time required will increase by the number of objects.
Top-Down detects the object first and then detect the specific keypoint. The accuracy of Top-Down models will be higher, but the time required will increase by the number of objects.
Differently, Bottom-Up detects the point first and then group or connect those points to form several instances of human pose. The speed of Bottom-Up is fixed and will not increase by the number of objects, but the accuracy will be lower.
| HRNet-w32 + DarkPose | Top-Down|256x192 | AP: 87.1 (on internal dataset)| 2.9ms per person |[Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.pdparams) |[Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip) | Especially optimized for fall scenarios, the model is applied to [PP-Human](../../deploy/pphuman/README_en.md) |
We also release [PP-TinyPose](./tiny_pose/README_en.md), a real-time keypoint detection model optimized for mobile devices. Welcome to experience.
To make users have access to models of different scenarios, PP-Human provides pre-trained models of object detection, attribute recognition， behavior recognition, and ReID.
| Task | Scenario | Precision | Inference Speed（FPS） | Model Inference and Deployment |
Action Recognition is widely used in the intelligent community/smart city, and security monitoring. PP-Human provides the module of skeleton-based action recognition.
...
...
@@ -12,11 +14,11 @@ used for academic research here. </center>
There are multiple available pretrained models including pedestrian detection/tracking, keypoint detection, and fall detection models. Users can download and use them directly.
Pedestrian detection and tracking is widely used in the intelligent community, industrial inspection, transportation monitoring and so on. PP-Human has the detection and tracking module, which is fundamental to keypoint detection, attribute action recognition, etc. Users enjoy easy access to pretrained models here.
# Multi-Target Multi-Camera Tracking Module of PP-Human
Multi-target multi-camera tracking, or MTMCT, matches the identity of a person in different cameras based on the single-camera tracking. MTMCT is usually applied to the security system and the smart retailing.
