ADAS & Driver Replacement: Machine Vision Algorithm Development & Simulation with MATLAB® Tools on S32V

File uploaded by Renee Fortenberry Employee on Jun 10, 2019Last modified by Renee Fortenberry Employee on Jul 2, 2019
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This session will provide a deep-dive technical session on how to develop, simulate and test machine vision algorithms with MATLAB toolsets like Computer Vision System and Image Processing on NXP S32V microprocessors. The MATLAB automatic generated code will be executed on the S32V234 SBC boards on Arm and APEX cores simultaneous to squeeze the best performance. The session will concentrate on feature detection for driver monitoring and will showcase various concepts like object detection using Viola-Jones, tracking a ROI using Kalman filters and various feature detection using Haar cascades classifiers. At the end of the session the participants will be able to develop from scratch complex algorithms for detecting various feature like: pedestrians, traffic signs, lane departure, etc. and do all these from a simple and user friendly environment like MATLAB.