Top Skills for Embedded Vision Engineers

Topic

This cutting-edge technology allows machines to “see” and “interpret” the world around them, opening up endless possibilities for innovation and creativity in a wide range of applications

What skills are necessary to thrive in this field?

First and foremost, a strong understanding of image processing and computer vision is essential. The former concerns performing operations on images to enhance or extract information from them. The latter studies techniques and algorithms to enable computers to recognize and understand images and scenes.

Secondly, you will also need to have a basic grasp of machine and deep learning concepts. The latter plays a crucial role in vision technologies today and is used, for example, to train algorithms enabling machines to recognize and classify objects.

Thirdly, as an engineer working with embedded vision, you will need enough skills to understand system architectures and operate with an optimization-oriented mindset. You will focus on using system hardware resources in the best possible way for your task (even programming at a low level if necessary), always seeking for the most efficient path, the best compromise among accuracy, performance and computational resources.

At EVS, we specialize in designing FPGA/ASIC solutions to accelerate computer vision and machine/deep learning algorithms in embedded applications. And if you’re interested in pursuing a career in embedded vision, we’ve got some tips to help you get started.

A few tips for expanding your embedded vision skills

As embedded vision engineers you will need multiple skills to operate in the intersection of artificial intelligence, computer vision, digital signal processing, and embedded systems.

A degree in Electronic Engineering, Computer Science, or related fields is certainly a good starting point but that is just the beginning – continuous learning and hands-on experience are essential to refine your skills and staying up-to-date with the latest technologies. Here are some top skills you should focus on developing:

  • Object-Oriented programming using modern C++ and Python.
  • Experience with embedded development/debugging and software optimization
  • Embedded Linux and Real-time Operating Systems (RTOS)
  • Device drivers, including Linux (user space/kernel space drivers)
  • Hardware description languages (VHDL, Verilog)
  • Solid understanding of Image Processing, Computer Vision, Machine and Deep Learning concepts
  • Understanding of design patterns and UML
  • Knowledge of computer and camera architectures
  • Software/Hardware partitioning. Hardware acceleration in FPGA, GPU, and DSP
  • Object-Oriented programming using modern C++ and Python.
  • Experience with embedded development/debugging and software optimization
  • Embedded Linux and Real-time Operating Systems (RTOS)
  • Device drivers, including Linux (user space/kernel space drivers)
  • Hardware description languages (VHDL, Verilog)
  • Solid understanding of Image Processing, Computer Vision, Machine and Deep Learning concepts
  • Understanding of design patterns and UML
  • Knowledge of computer and camera architectures
  • Software/Hardware partitioning. Hardware acceleration in FPGA, GPU, and DSP

The key driver is passion

Building these skills takes a lot of time and practice, but it is a rewarding path that can lead to significant professional achievements.

To expand your skillset, consider taking online courses, reading books and webinars, and most importantly, seeking out hands-on experience in areas you’re passionate about. Do not underestimate the power of mentorship or internships.

The guidance of someone who has mastered the skill you’re trying to develop can be incredibly valuable and accelerate your understanding of the field.

by evs_admin