The world is growing and faster than ever. Scientist predict we will cross 9B people this century. And while there are arguments about when that growth will stop and how quickly, one thing is clear: we are going to run out of food soon. Recent research proposes that in order to accommodate such a large population, we are going to have to change our diet. Specifically, move away from meat and consume mostly (if not exclusively) fruit and vegetable. Meat consumption has dire effects on the environment. It is expensive to grow, raises moral concerns, but primarily it is extremely ineffective. An ..read more

I’ve bee involved in the current generation of Virtual Reality from early on. You can read more about that in my website [Dov Katz]. There are many exciting problems related to VR and computer vision but one that I always found exciting is that of reconstructing a room from a single image. All in all, humans seem to be pretty good at it. It is clear that we are good at estimating the true structure of a room because we have so much experience with rooms and the objects in it. Now, can machines do the same? In a recent paper titled “LayoutNet: Reconstructing the 3D Room Layout from a Single RGB ..read more

Tracking the 6D pose of an object is an important task with many applications. For example, it’s a key component for AR, VR and many robotics systems. There are many approaches to solve this problem. For example, when you know something about the size of the object and trackable features on it. Or, when the tracked object is a moving camera (ie. SLAM). These techniques all rely on the stereoscopic vision principle (directly or indirectly). They basically relate multiple views to compute depth. The main issue with such methods is objects that are weakly textured, low resolution videos and low l ..read more

When my wife Gili Katz and I were looking for a house, we would have loved to have the option to check out a few options in VR. You can check out my website (Dov Katz) for more info about Virtual Reality. Here’s about some recent development that make virtual real estate shopping a possibility: Shopping for real estate can be quite frustrating. You need to search ads for what seems like the right place for you, then contact agents, schedule appointments, drive and finally walk-through the house for a few minutes. If it doesn’t seem very effective, it’s because it isn’t. Fortunately, comp ..read more

Deep Neural Networks have enabled tremendous progress in computer vision. They help us solve many detection, recognition and classification tasks that seemed out of reach not too long ago. However, DNNs are known to be vulnerable to adversarial  examples. That is, one can tweak the input to mislead the network. For example, it is well documented that small perturbations can dramatically increase prediction errors. Of course, the resulting image looks like it was artificially manipulated and the process can be mitigated with de-noising techniques. In this paper the authors propose a new cl ..read more

Deep learning is a development on top of the classical neural network architecture that was all the rage in the 80s. Following a long AI winter , deep learning is emerging as a successful technique. In particular, it already showed impressive results in the domain of computer vision. Deep learning, as the name implies, is a neural network architecture composed of multiple layers. Advancement in compute and the availability of large amounts of data via the internet are the key enablers. To appreciate deep learning, you really should pick a book or take a class. This tutorial is more practi ..read more

There are so many cool areas where computer vision can make a difference. We typically think about autonomous cars, robotic manipulators, or face recognition. But there are so many other areas. One of them is agriculture. Computer vision can make certain tasks easier, more efficient and more accurate. This could lead to cheaper and more available food supply. Here’s a short review of a paper by Oppenheim et al. from Ben-Gurion University in Israel. You can find the publication here. Paper overview Oppenheim et al. write about using computer vision techniques to detect and count yellow tom ..read more

Change blindness is a perceptual phenomenon that occurs when an observer fails to notice a visual change. There are multiple ways to distract an observer such that change is not being noticed. Those include image flickering, gradual change and other distracting changes in the scene. I find change blindness fascinating not because it shows the failings of human perception but because it reveals the inner workings of our visual system. Think about entering a new room: We immediately take in the entire scene. It feels like we see everything and know what every object in the image is right away ..read more

Image processing was for a long time focused on analyzing individual images. With early success and more compute power, researchers began looking into videos and 3D reconstruction of the world. This post will focus on 3D. There are many ways to get depth from visual data, I’ll discuss the most popular categories. There are many dimensions to compare 3D sensing designs. These include compute, power consumption, manufacturing cost, accuracy and precision, weight, and whether the system is passive or active. For each design choice below, we’ll discuss these dimensions. Prior Knowledge The most ba ..read more

A reoccurring problem in computer vision has to do with finding the precise location of an object in the image. In this post, I want to discuss specifically the problem of finding the location of a blob or a point in an image. This is what you’d get when a light source is imaged. Finding the center of the blob is a question I love asking in job interviews. It’s simple, can be solved with good intuition and without prior knowledge, and it shows a lot about how one grasps the process of image formation. What’s a blob? A blob is what’s formed on an image plane when imaging a light source. Fo ..read more