A look at the most talked-about machine vision technologies, their practical uses and limitations, and which will have a long-lasting impact on your current and fixture applications.
“What’s trending?” is a phrase that has become ubiquitous in our social and business consciousness. A trend is a prevailing tendency that might (or might not) have long-term implications. What’s #trending on Twitter can be so fleeting that by the time you mention it someone will say “that’s so last hour’s news.” Alternately, something that was a trend may cease being “trendy” and become essential (e.g. computers, internet, smart phones, etc.). Trends can be based on statistical evidence (sales numbers, market results, YouTube views), molded by prevailing opinion, or even built by media coverage or marketing initiatives that create buzz around a product or idea.
For this discussion, “What’s trending?” in machine vision comes from personal observation—and opinion—of the market and the level of publicity apparent in recent media and marketing. To be clear, most trends in machine vision originate with competent and useful new or evolving technologies. However, in an engineering discipline like machine vision, a further consideration that seems appropriate is whether a trend is based on current practical use cases or on extreme forward-looking predictions of future capability that are not yet fully realized. For example: statements like “most homes will have a service robot” or “your consumer electronics will contain an embedded vision system for facial or gesture recognition” certainly may be true eventually but labelling these as current trends in robotics or vision is premature. The challenge for machine vision users and solutions providers, then, is to understand what specific applications can benefit now from a given trending technology, and to avoid the trends that are not viable in the short term or not a good fit over the long-term for their application(s).