Video is an extremely popular way to represent information. Indeed, sometimes it is enough to watch a short clip instead of long listening or reading about complicated technical concepts. From a user’s point of view, a video is just a sequence of images followed one-by-one with a very short inter-frame interval. Typically it has around 30 frames per second (FPS). However, many things are left inside the box.
Long time no meetup, right? We’re fixing it with our joint online event with Sigma Software University on October 28 😉 Computer vision for faces… One of our favorite topics! Today, almost every image and video contain faces (thank you, selfies!), and computer vision and deep learning algorithms become a common thing in face processing.
Deep learning (DL) and neural networks are extremely widespread in different computer vision (CV) applications. Indeed, many typical problems (like object recognition or semantic segmentation) are effectively solved by convolutional neural networks (CNNs). In this article, we are going to discuss how to utilize CNNs on embedded devices. Neural networks today are ubiquitous. In particular, it is hard to imagine computer vision without them.
