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’.
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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.
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.
Let’s recap some of the most important topics we’ve covered about treating an image as a matrix within MATLAB which we can display or index into.
We can use MATLAB to display a profile of brightness along a line in the image.
We learn how to describe the orientation of an object by a 2×2 rotation matrix which has some special properties. Try your hand at some online MATLAB problems. You’ll need to watch all the 2D “Spatial Maths” lessons to complete the problem set.
We learn how to use information from three magnetometers to determine the direction of the Earth’s north magnetic pole.
When matching points between scenes with large different viewpoints we need to account for varying image size and rotation. SIFT features are a powerful way to achieve this.
We resume our analysis of the 6-link robot Jacobian and focus on the rotational velocity part.
We consider the simplest possible robot, which has one rotary joint and an arm.