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Motion field

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  • 3 chapters

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Through Computer vision, Motion and Camera

Introduction

A camera model maps each point (x1,x2,x3) in 3D space to a 2D image point (y1,y2) according to some mapping functions m1,m2:

(y1y2)=(m1(x1,x2,x3)m2(x1,x2,x3))

Assuming that the scene depicted by the camera is dynamic; it consists of objects moving relative each other, objects which deform, and possibly also the camera is moving relative to the scene, a fixed point in 3D space is mapped to varying points in the image. Differentiating the previous expression with respect to time gives

(dy1dtdy2dt)=(dm1(x1,x2,x3)dtdm2(x1,x2,x3)dt)=(dm1dx1dm1dx2dm1dx3dm2dx1dm2dx2dm2dx3)(dx1dtdx2dtdx3dt)

Here

u=(dy1dtdy2dt)

is the motion field and the vector u is dependent both on the image position (y1,y2) as well as on the time t. Similarly,

x′=(dx1dtdx2dtdx3dt)

is the motion of the corresponding 3D point and its relation to the motion field is given by

u=Mx′

where M is the image position dependent 2×3 matrix

M=(dm1dx1dm1dx2dm1dx3dm2dx1dm2dx2dm2dx3)

This relation implies that the motion field, at a specific image point, is invariant to 3D motions which lies in the null space of M. For example, in the case of a pinhole camera all 3D motion components which are directed to or from the camera focal point cannot be detected in the motion field.

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