FPGA Based Real Time Human Crowd Motion Classification Demo
- 9 years ago
This video demonstrates a real time implementation of FPGA Based Human Crowd Motion Classification System.
It classifies the human crowd behavior using motion vectors statistical features and categorizes them into 'Panic/Fighting, Normal/Swift Walking, Running, Fast Running' etc.
It also detects whether people are diverging or their motion momentum has changed in the scene.
The hardware used is Spartan-6 ATLYS FPGA board and the over all application built uses Xilinx ISE, Vivado HLS, and Embedded Development Kit.
It classifies the human crowd behavior using motion vectors statistical features and categorizes them into 'Panic/Fighting, Normal/Swift Walking, Running, Fast Running' etc.
It also detects whether people are diverging or their motion momentum has changed in the scene.
The hardware used is Spartan-6 ATLYS FPGA board and the over all application built uses Xilinx ISE, Vivado HLS, and Embedded Development Kit.