Sramana Mitra: How does your technology correlate these products? Is this where your ability to do image analysis kicks in?
Stephanie Newby: Image analytics is still a little young. Most of the image analytics that’s currently being used in the platform is logo recognition. If you were in Starbucks and you took a photograph of yourself, we could identify that that was a Starbucks logo. Starbucks, as a company, can find all the places where their logo has been caught in a snapshot.
Without the logo, we are actually working on the ability to identify trends in fashion, for example, based on what people are wearing or what’s creating buzz at events like the New York Fashion Show. If a particular hairdo was worn, and if we can see that somebody has snapped a particular photograph of a model with a hairdo, that would be very interesting to know early on in an event like that because the designers could capitalize on it immediately, rather than having a wasted opportunity. That’s where we’re headed.
Our R&D team is working on being able to detect emotion on people’s faces from the photograph. That’s all the nascent innovation, but today it’s really more about logo detection.
Sramana Mitra: It’s interesting because if you look at the convergence of mobile and social, which I believe have converged very significantly, the bulk of that has actually happened around images. When it comes to visual merchandising of any kind, whether it’s in stores or even the street, the ability to pick up those signals that are in those images is going to become a critical phenomenon in being able to extract meaning and sentiment out of that social and mobile interaction.
Stephanie Newby: That’s right. We’ve been able to take image analytics for quite a long time on the platform, but the way it started several years ago was by analyzing the text in captions associated with the photograph. The new wave is really being able to analyze what’s going on in the photograph itself.
Sramana Mitra: What is the state of the industry as it pertains to image analytics? You are doing some R&D. Are there other players who have technologies in this area that is interesting?
Stephanie Newby: I think there’s a lot of people experimenting with image analytics. Some of them are very small companies. A couple have been bought recently by larger companies. That’s really the hot topic right now.
Sramana Mitra: My last question is if you lift yourself to the 30,000 foot level, talk about some opportunities to go solve open problems in the Mobile and Social space, where would you point them to? I’m asking you this question after this discussion of Image Analytics. It sounds like Image Analytics is a hot area and has a lot of open problems.
Stephanie Newby: I think the things that we have not talked about might fit this context, which is video. Video is extremely complex. It uses even more bandwidth than photograph. Video comes in all different lengths. The short videos would be easiest for people like ourselves to be able to get a foothold in there or start with development there. That’s only one very small sliver of the video market. That scenario is a complete green field.