| Model Type | Pose Estimation |
|---|---|
| Framework | AI Edge LiteRT, OpenVINO |
| Algorithm | PoseNet MobileNet |
| Technical Details | Estimates human body keypoints and poses for single or multiple people, supporting real-time monitoring and vision-based applications. |
PoseNet for Multi-Person Pose Detection
Lightweight and quantized PoseNet model for real-time multi-person pose estimation on edge hardware.
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PoseNet for Multi-Person Pose Detection
app details
Resources
Use Cases
Industrial Safety
Surveillance
Supported SECO Devices
AI optimized hardware
Fanless embedded PCs
Modules
supported chipsets
Intel® Core™ i3
Qualcomm® Dragonwing QCS6490
Qualcomm® Dragonwing QCS5430
NXP i.MX 8M Plus
NXP i.MX 95
Performance Benchmark
Hardware · Backend
Processing unit
Latency (ms)
Avg. Peak RAM
Intel Tiger Lake · OpenVINO
GPU
8.5 ms
527.3 MB
Intel Tiger Lake · OpenVINO
CPU
11.4 ms
448.4 MB
Intel Tiger Lake · AiEdgeLiteRT
CPU
15.2 ms
85.3 MB
MediaTek Genio 510 · AiEdgeLiteRT
CPU
53.4 ms
78.5 MB
NXP i.MX 8M Plus · AiEdgeLiteRT
NPU
27.2 ms
76.1 MB
NXP i.MX 8M Plus · AiEdgeLiteRT
GPU
27.2 ms
76.2 MB
NXP i.MX 8M Plus · AiEdgeLiteRT
CPU
545 ms
76.2 MB
Qualcomm QCS6490 · AiEdgeLiteRT
NPU
2.8 ms
80.9 MB
Qualcomm QCS6490 · AiEdgeLiteRT
CPU
55.7 ms
76.9 MB
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