Multi Object Detection Reference Design

Edge AI Accelerated Object Detection On FPGA

This Multi Object Detection (MOD) reference design enables real-time detection, classification, and tracking of multiple objects in images and video streams at the edge. Built on the Lattice CertusPro-NX FPGA System-on-Module (SOM), the design integrates compute, memory, connectivity, and AI acceleration for robust, low-power vision intelligence in industrial, robotics, automotive, and smart camera applications.

The MOD reference design supports:

  • Simultaneous detection and tracking of multiple object classes
  • Dynamic overlay of bounding boxes and labels on video output
  • Scalable architecture for high-resolution image processing
  • Seamless integration with host processors (e.g., Raspberry Pi CM5) via MIPI and I2C
  • Flexible deployment for counting, classification, and defect detection use cases

Features

  • Identify and track several objects at once, even in dynamic or crowded scenes
  • Efficient AI models optimized for edge devices, enabling always-on operation
  • Identify and track several objects at once, even in dynamic or crowded scenes
  • Supports a wide range of object classes and deployment scenarios
  • Easily connects to existing infrastructure and legacy systems
  • Accurate detection and tracking for safety-critical and monitoring applications

Block Diagram

Multi Object Detection Reference Design

Documentation

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Multi Object Detection Reference Design and Demonstration Documentation
To learn more about this product design and to access the complete source code, bitstream and user guide in GitHub, please click here
1/18/2026 WEB

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