“Robot vision” brings Terminator images to mind. For whatever reason, Google Image searches for “robot vision” bring up a lot of red, gleaming, glowing eyes that seem signal human doom.

Fortunately, the startups in this space are working on anything but evil killer robots.

That’s not what Pierre Cambou at has in mind. I was able to catch up with Pierre recently with regards to his upcoming projects in the field of machine vision, and glean some inside insight into the possibilities and future trajectory of machine sight and sensor technology.

The advent of massive investments and developments in telecom has driven the quality of sensors up and the prices of sensors down, says Pierre. As of now, research is robots is often left to fund itself, but cell phone companies are cranking out massive profits and are capable or dumping tons of that cash back into R&D. Samsung wants to brag about a better camera than the iPhone, and vice-versa, and unlike many robotic vision technologies, cell phones have a clear, defined, and massive market.

Pierre’s company, Vence Innovation (website no longer live), is taking advantage of these developments in sensor technology and is aiming to apply them in unique ways to different sectors.

One application that the team is working on – that Pierre feels is a strong application for machine learning overall – is the field of assisted living. Japan’s concerns about dropping birth rates (and their fascination with robots) has produced a wave of innovation in the field of assisted living, which has also developed the assisted living robotics industry in Europe. Pierre believes that better vision and sensors could detect the movement and behaviors of an elderly individual without needing to place them under constant visual surveillance.

The robot would need to detect unusual movements, calls for help, or falls and injuries, and immediately call for help or come to the aide of the elderly person themselves – all with the help of more capable vision sensors. Pierre believes that these technologies have serious implications for the livelihood of our elderly, and that they may be an overlooked area for the direct application of improved machine vision and perception.

Another potential application for visual sensors in a public store or market area would be for statistics on customer frequency and behavior. Pierre suggests that “robot eyes” in a storefront environment can do more than monitor security. The technologies he would be working on would be able to detect the number of people entering a store during different times of the day, week, or season, as well as pick up on behavior trends.

Imagine running a storefront and getting accurate data on the percent of consumers who enter your store in different whether conditions, times of the day, or with different store-front displays / signage.

Imagine knowing which displays tend to keep people active in your store for the longest amount of time, and being able to track that information with revenue, or make comparisons with people of different ages, or between men and women.

Imagine being in charge of marketing for a chain of shops and being able to find display and in-store setups that tended to have the highest success rates across locations.

This is more like big data than big brother, though admittedly, the two have some serious opportunities for cross-over.

One thing is clear, however, and that’s that sensors are picking up steam like never before – and some experts believe this to be the harbinger of a serious revolution in robotics. Though only the future will tell if this is in fact true, it certainly doesn’t seem to hurt the progress of robotics, and startup founders like Pierre are aiming to widen the field as much as possible.

Image credit: TurboSquid

MARKET RESEARCH x INDUSTRY TRENDS

TechEmergence conducts direct interviews and consensus analysis with leading experts in machine learning and artificial intelligence. Stay ahead with of the industry with charts, figures, and insights from our unparalleled network, including executives from Facebook, Google, Baidu, Yahoo!, MIT, Stanford and beyond: