Face Tracking

Lattice sensAI Reference Design

This reference design provides an example of how to implement a face/object tracking application based on the Lattice sensAI stack. It includes a SPI, DDR memory interface IP blocks, an image signal processing engine, 8 CNN acceleration engines and an overlay engine to indicate the face in the image.

The reference design is optimized for the ECP5-85K FPGA. While the FPGA logic will be loaded from the external flash memory, the weights and biases are loaded from a SD card, connected to SPI interface.

Features

  • Green box indicates location of face in image
  • Runs @ 14fps with 90 x 90 RGB input
  • Consumes 0.85W of power consumption on ECP5 FPGA
  • Applications include selfie drones, surveillance cameras, smart cameras etc
Lattice sensAI

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Video

Face Tracking Using ECP5 and CNNs

  • This demonstration identifies and tracks a human face
  • The inferencing is done using Convolutional Neural Networks implemented in the Embedded Vision Development Kit’s ECP5 FPGA
  • Power consumption is less than 1W

Block Diagram

Face Tracking Block Diagram

Documentation

Technical Resources
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Face Tracking Using CNN Accelerator IP - Documentation
FPGA-RD-020371.25/19/2021PDF1 MB
Face Tracking Using CNN Accelerator IP Code
1.19/25/2018ZIP146.4 MB

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