Bay Vision - Spring 2018

these challenges over a long period of time. The season lasts six months and variations in illumination can happen day- to-day, from geographical area to geographical area. How do they solve it? Ara explains: “ In my opinion, the best way to solve these variations in illumination condition is by understanding the images. Start from an image formation model. The fields that we are analyzing, they’re all described by a similar set of parameters, which are the vegetation rows that are all equidistant and parallel. Rather than doing a blind image segmentation, we start from the underlying knowledge that this is what the image looks like . We start from an image formation model and we adapt the parameters of the segmentation that best fit this image model. Using our prior knowledge about the image within a statistical framework certainly helped us a lot in dealing with global illumination variations. ” Finally, Ara tells us about the excitement the whole team has for this work: “ You wake up in the morning and the first thing you do, instead of checking your phone, you look for the weather in Iowa and Illinois where we fly to see if it’s a good day for flying. Next, you talk to the flight operators to see that the pilots are all flying and there are no issues, no clouds. Then a few hours later you see the data come in and within 24 hours you are passing it to the farmers. I think that’s the thrill that comes with a beautiful product, a great problem to tackle and to solve, and certainly the excitement that you see from the satisfaction of our customers . I guess that’s the great thing about working in a start-up. ” 23 IntelinAir Bay Vision