Machine Vision Algorithm Development Using Vision Toolbox

Learn how to develop, simulate and test machine vision complex algorithms with MATLAB^® toolsets like computer vision system and image processing on S32V vision processors to detect different features (like pedestrians, traffic signs or lane departure).

The session focuses on feature detection for driver monitoring systems (DMS) and will showcase different concepts like object detections using Viola-Jones, tracking a region of interest using Kalman filters and some feature detection using HAAR cascades classifiers. The MATLAB automatic generated C++ code will be executed on the SBC-S32V234 Evaluation Board for Vision and Sensor Fusion on Arm^® and APEX cores simultaneously to squeeze the best performance.

• S32V Introduction
• MathWorks Ecosystem
• Embedded System Development Process with MATLAB
• NXP VISION Toolbox for S32V
• Object and Feature Detection Demo
• CNN SqueezeNet Demo

• How to develop, simulate and test machine vision complex algorithms with MATLAB^® toolsets on S32V.

• S32V2 Processors
• S32V Vision and Sensor Fusion Evaluation Board