To help machines learn what we human beings are doing via a camera is important. Once it comes true, machines can make different responses to all kinds of human's postures. But the process is very difficult as well, because usually it is very slow and power-consuming, and requires a very large memory space. Here we focus on real-time posture recognition, and try to make the machine "know" what posture we make. The posture recognition system is consisted of DE10-Nano SoC FPGA Kit, a camera, and an HDMI monitor. SoC FPGA captures video streams from the camera, recognizes human postures with a CNN model, and finally shows the original video and classification result (standing, walking, waving, etc.) via HDMI interface.
Stars
55
Forks
15
Watchers
55
Open Issues
0
Overall repository health assessment
No package.json found
This might not be a Node.js project
16
commits
:memo: add samples for training cnn of posture recognition
a0c9ad9View on GitHub2018-05-01: add IP core (in altera Quartus) into the repo
1a99cc9View on GitHubmodify the thesis[ add NPU error figure], and ppt [add QRs]
51874e3View on GitHub2018-04-26: add documents(ppt&thesis), projects(FPGA,matlab,python)
6f7751fView on GitHub