Feature: Sensor Technology
Flipping human motion detection
on its head By Gabriele Fulco, product marketing manager, Omron Electronic Components Europe B.V.
Omron’s Gabriele Fulco explores what it is that makes humans so difficult to reliably detect, and how successfully navigating these obstacles could usher in a new era of productivity. Efforts to mimic human vision to
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identify objects are nothing new. Te first digital image processing technologies were first developed in the 1960s, and have been constantly refined and improved ever since. Recent advances in AI have served to intensify these efforts further. Achieving a computer-based vision system that cannot just match but exceed the accuracy and understanding of human vision combined with a human brain has been notoriously difficult. Unlocking this technology could potentially herald a revolution in human progress, revolutionising everything from agriculture to medical science, as well as industrial operations. Te human body is the product of hundreds of thousands of years of
10 October 2024
www.electronicsworld.co.uk
utomatic object detection is growing ever more sophisticated, yet the accurate detection of humans still poses unique challenges.
diversity of humans themselves make them one of the most challenging subjects to reliably detect without training any system extensively on specific individuals. Even a change of clothing or hairstyle
evolution, and as such is incredibly sophisticated. Computers have long been able to detect and understand 2D pictures, but dynamic three-dimensional environments are a step far beyond this. Indeed, human vision is not just about simply perceiving the world around us; it is also about understanding it. Our brains are able to constantly provide the vital contextual information to allow us to make sense of our surroundings in real-time. Computers have traditionally been unable to match this level of sophistication, that is until recently. Training a machine to not only perceive
but understand the world around it presents complex technological and computational challenges. Detecting humans adds yet another layer of complexity. Indeed, the uniqueness and
can present problems. When you add in additional factors such as the wider environment with which humans are interacting, combined with the unpredictability of human behaviour, the technical challenges quickly mount up. Any viable solution also has to be cost- effective and economical in size in order to be practical in everyday environments. Solving these problems is not easy. In
fast-moving industrial settings for instance, several humans may all be working at speed, carrying out various different duties within the same space. Attempting to track their movement from a side-on or even an isometric view has traditionally proven an imperfect solution, as this requires the system to have an understanding of the depth of vision. In a single-camera configuration, one person can also very easily obscure another from view and create blind spots. In addition, one of the major challenges in the development of vision sensing
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