Summary of Advanced Image Processing Operations
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Let’s recap the important points from the topics we have covered in advanced image processing.
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Let’s recap the important points from the topics we have covered in advanced image processing.
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The orientation of a body in 3D can also be described by two vectors, often called the approach and orientation vectors.
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The orientation of a body in 3D can also be described by a unit-Quaternion, an unusual but very useful mathematical object. In the MATLAB example starting at 3:48 I use the Quaternion class. For Toolbox version 10 (2017) please use UnitQuaternion instead.
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The orientation of a body in 3D can also be described by a single rotation about a particular axis in space.
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The pose of an object can be considered in two parts, the position of the object and the orientation of the object. Try your hand at some online MATLAB problems. You’ll need to watch all the 2D “Spatial Maths” lessons to complete the problem set.
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Many scenes, particularly of man-made environments, have very dominant lines due to the edges of objects. The Hough transform is a common technique for finding dominant lines, and we ill examine how it works and apply it to a real image.
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We consider a robot, which has two rotary joints and an arm.
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As the illumination level changes so do the red, green and blue tristimulus values, but they are linearly related. We can separate brightness from chromaticity which is a two dimensional representation of color. We discuss briefly the effect of gamma encoding on the color reproduction process.
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We resume our analysis of the 6-link robot Jacobian and focus on the rotational velocity part.
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We learn how to create smoothly varying orientation in 3D by interpolating Euler angles and Quaternions. In the MATLAB example starting at 5:44 I use the Quaternion class. For Toolbox version 10 (2017) please use UnitQuaternion instead.