Learning to Develop Embedded Vision Applications for Object Detection and Feature Tracking
The ability of computers to recognize objects is one of the most exciting sides of Artificial Intelligence (AI). Deep Learning-based Computer Vision software helps to solve Industry 4.0 and automated vehicle challenges by minimizing human intervention, providing a real-time solution for industrial and automotive applications, reaching an overall market value of USD 17.38 Billion by 2023.
This webinar will show you step-by-step how to get your vision application up-and-running in less than 15 minutes using the complimentary NXP S32 Design Studio IDE and the NXP Vision SDK with Image Sensor Processor (ISP) and APEX graph tools. Example codes for Feature Tracking and Object Detection will be used during the session to show you the straightforward development process of vision applications.
Attendees will learn:
- To develop Vision applications with APEX CV libraries, using examples of Lucas-Kanade optical flow and GFTT algorithms
- To use NXP S32 Design Studio IDE, Vision SDK, ISP and APEX graph tools to run vision applications using NXP S32V234EVB and MIPI based camera
Phil Pesses, Senior Technical Product Marketing Engineer – Automotive Microcontrollers and Processors, NXP Semiconductors
Phillip Pesses is a product marketing professional with more than 15 years of experience with a strong understanding of ADAS systems. He is responsible for the product marketing and go-to-market plans for microcontrollers targeted for the automotive and distribution markets.He has a Bachelor's Degree in Electrical Engineering from the University of Texas at Austin.
Kushal Shah, Systems & Applications Engineer – Automotive Microcontrollers and Processors, NXP Semiconductors
Kushal Shah is an experienced automotive engineer focused on high-performance computing and machine learning solutions. He has a Bachelor's Degree in Electronics Engineering from the M. S. University of Baroda and holds a Master's Degree in Computer Engineering Science from the University of California, Riverside.