Given two images of a scene taken from slightly different viewpoints, a stereo image pair, it’s possible to determine the disparity for every pixel using template matching. The disparity image is one where the value of each pixel is inversely related to the distance between that point in the scene and the camera.
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Humans have long been fascinated with seeing images and movies in ‘3D’. Let’s look at how human stereo vision works and some of the technologies used to present images to our eyes in ‘3D’.
Let’s recap the important points from the topics we have covered about human depth perception, display of 3D images and estimating 3D scene structure using stereo and other types of sensors.
One very powerful trick used by humans is binocular vision. The images from each eye are quite similar, but there is a small horizontal shift, a disparity, between them and that shift is a function of the object distance.
We use MATLAB and some Toolbox functions to create a robot controller that moves a camera so the image matches what we want it to look like. We call this an image-based visual servoing system.
A critical part of a visual servoing system is establishing correspondence between points in the scene observed by the camera, and points in our desired image of the scene.
The relationship between world coordinates, image coordinates and camera spatial velocity is elegantly summed up by a single matrix equation that involves what we call the image Jacobian.
For a binary image that contains multiple blobs we must first transform it using connectivity analysis or region labeling. Then we can describe each of the blobs in the scene we first need to transform the image using connectivity analysis. Each of the blobs can then be described in terms of its area, centroid position, […]
Diadic operations involve two images of the same size and result in another image. For example adding, subtracting or masking images. As a realistic application we look at green screening to superimpose an object into an arbitrary image.
If we want to process images the first thing we need to do is to read an image into MATLAB as a variable in the workspace. What kind of variable is an image? How can we see the image inside a variable? How do we refer to to individual pixels within an image.