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Kinect Image Manipulation Project

Kinect Image Manipulation Project. CSC410 Victor Milenkovic , Justin Stoecker , Brendan Loyot. Project Overview. Build a system to manipulate 3d images on a screen with the Kinect device. 1 st steps are to build up a set of gestures that the K inect recognizes.

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Kinect Image Manipulation Project

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  1. Kinect Image Manipulation Project CSC410 Victor Milenkovic, Justin Stoecker, Brendan Loyot

  2. Project Overview • Build a system to manipulate 3d images on a screen with the Kinect device. • 1st steps are to build up a set of gestures that the Kinect recognizes. • Key input in form of a depth map. • Recognize gestures by using statistical and physics methods. Key properties: Depth map, histogram, standard deviation, principal moments and axes of inertia.

  3. Depth Map • Values processed by the Kinect and received by this system. • 2D array. The X,Y axes match the X,Y positions of a given pixel and the value and X,Y is the Z position (i.e. depth). • From this we have a 3d representation of a pixel.

  4. Sample Depth Map

  5. Histogram • A histogram is a graph of the frequency with which a value occurs in a set. For our goals, we will create a histogram mapping the frequency of Z values. • We expect to see a spike in the histogram at 2 points: the Z range of the hand and the Z range of the wall. • We can isolate those pixels which belong to the hand by looking at this first spike.

  6. Sample Histogram

  7. Standard Deviation • The standard deviation represents how “spread out” a distribution of points is. • We can use this to determine whether the hand is open or closed, for example. With the hand open, we expect a larger standard deviation, and with the hand closed, we expect smaller.

  8. Inertia Tensor • If you don’t have given axes of rotation, you can create a generalized 2nd order tensor for the scalar moment of inertia. • For the Inertia Tensor when i=j, represents the moment of inertia around the X,Y,Z axes when the object is rotated around the X,Y,Z axes. For the other 6 terms, represents the moment of inertia around the ith axis when the object is rotated around the jth axis.

  9. Principal Moments and Directions of Inertia • Spectral Theorem says that there exists a coordinate system where • Essentially, this coordinate system is balanced around the symmetry of the object. • In this matrix, are the principal moments of inertia, and the axes with which this coordinate system was built are the principal axes.

  10. Eigenvalues and Eigenvectors • The process of finding this diagonalized matrix I and the axes of inertia involves a linear algebra technique for finding Eigenvalues and Eigenvectors. • Solving yields 3 values for

  11. Eigen values and vectors cont. • Solving Where is one of the 3 given’s above yields 3 Eigenvectors. The Eigenvalues correspond to the principal moments of inertia and the eigenvectors correspond to the principal axes.

  12. Importance of these inertial values • Once we have the moments of inertia, we can infer several valuable pieces of information. • For example, information about the rotation of the hand can be found from the angular momentum • The kinetic energy can be used to find the magnitude of movements of the hand.

  13. Current output

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