## 9 – Histogram of Oriented Gradients

In computer vision there are many algorithms that are designed to extract spatial features and identify objects using information about image gradients. One illustrative technique is called HOG or Histogram of Oriented Gradients. Histogram of Oriented Gradients may sound a little intimidating. So let’s go through what these terms actually mean. A histogram is a … Read more

## 8 – 08 ORB In Video V2 (1)

One common use for ORB, is in tracking and identifying objects in real time video streams. In this case, we compute the ORB descriptors for any images or objects we want to detect, before seeing a video stream and save those descriptors. Then, for each frame in an incoming video stream, we calculate ORB descriptors … Read more

## 7 – 07 Feature Matching V2

Now that you know how the algorithm works you may be wondering how exactly can we use ORB descriptors to perform object recognition? Let’s look at an example that displays how ORB can detect the same object at different scales and orientations. Suppose I want to be able to detect this person’s face in other … Read more

## 6 – 05 Scale And RotationInvariance V2

ORB uses fast to detect key points in an image. And it goes to a couple of extra steps to make sure that it can detect objects no matter their size, or location in an image. Given an image, the ORB algorithm starts by building an image pyramid. An image pyramid is a multi-scale representation … Read more

## 5 – 04 Brief V4

The second part of the orb algorithm is to take the key points found by the first algorithm and turn those into feature vectors that together can represent an object. To create feature vectors, orb uses the BRIEF algorithm. BRIEF stands for binary robust independent elementary features, and its purpose is to create binary feature … Read more

## 4 – 03 Fast V3

The first step in ORB feature detection is to find the key points in an image, which is done by the FAST Algorithm. FAST stands for Features from Accelerated Segments Test, and it quickly select key points by comparing the brightness levels in a given pixel area. Given a pixel, which I’ll call p in … Read more

## 3 – 02 Introduction To ORB V3

Orb, stands for Oriented Fast and Rotated Brief. Fast and brief, are a feature detection in a vector creation algorithm respectively. And we’ll get into the math behind each of these algorithms in the next couple of videos. Orb, starts by finding special regions in an image called key points. In general, you can think … Read more

## 2 – 01 Realtime Feature Detection V2

Having a fast Object Recognition Algorithm is essential for many computer vision applications, such as an augmented reality, robotics and self-driving cars. These kinds of applications need to respond to input video streams in real time, and so time is critical. A self-driving car for example, needs to constantly check whether another cars in front … Read more

## 1 – Feature Vectors

Now you’ve seen that corners are good unique features that can help identify certain points on an object. And this is a great example of how object structure and image gradients can be useful in feature recognition. But if we’re interested not only in feature points like corners, but in whole object detection, we have … Read more