Did you know that human faces are capable of more than 10,000 different expressions? Can facial expressions or even the slightest quirks be captured and analysed in real time? This may sound incredible, but several companies are already using technology to capture and measure human emotions.
This has tremendous commercial implications for companies in the consumer space as it helps them analyse and use that information to market their products or services better. Take the case of a company, which is a leading authority on emotion detection and sentiment analysis technologies, and provides an API that enables real-time emotional analysis—ensuring accurate readings of positive, negative, and neutral emotions. The API can measure 28 facial actions—right from eyebrow raises, nose wrinkles, and lip curls to jaw drops.
Another provider in the emotion-enabled technology space, offers an interactive demo through which it measures and captures key user emotions. It then processes the emotional feedback and reports the findings to the moderator for a follow-up discussion. This could be a boon for companies operating in online retail.
In addition to measuring and analysing human emotions, face analytics technology is widely used in other areas as well. For instance, it can also be used to identify your age, black out inappropriate content in social networks, identify friends’ Facebook photos or even let employees check in and out without an access card.
Technology advancements in this area have been a boon for law enforcement agencies. On an average, it takes a forensic examiner two to five days to conduct an exhaustive examination of a standard home computer for child pornography. But ‘Artemis’— a facial analytics system— performs a scan in minutes that outputs a forensic report, tagging potentially illegal videos or images on the suspect computer or memory device.
Several companies operating in the social media space also use facial analytics to uniquely position their services. A “hangout” platform allows its members to introduce new friends using an algorithm that leverages face detection analytics to match them by age. It also flags members accessing age-inappropriate parts of the site or those showing inappropriate images in the video chat section. In another example, a leading dating community portal uses the same detection analytics to establish matches based on the similarity of appearance.
Not to be left behind, some companies are also putting facial recognition to practical use in the office environment. For example, employees at one construction site check in and out without having to swipe in—using an app that requires a database of employee names matched with photos.
Although companies operating in this space proclaim to only look at characteristics such as gender, mood, age, or facial expressions and refrain from sharing any personal information, concerns on privacy remain. Hence the proliferation or widespread use of this technology will depend on how companies successfully address public concerns regarding privacy.