Firefly Eindhoven - Remaining Sensors: Difference between revisions
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'''Working Principle''' | '''Working Principle''' | ||
<math>I(x,y,t) = I(x+dx, y+dy, t+dt)</math> | If <math>I(x,y,t)</math> is a pixel in an image then after some time <math>dt</math>, as the pixel moves some distance <math>dx</math> and <math>dy</math> then as the pixel intensity is consistent, it can be said that; | ||
<math>I(x,y,t) = I(x+dx, y+dy, t+dt)</math> | |||
Using taylor series, it is possible to write | Using taylor series, it is possible to write | ||
<math> | <math> \frac{\partial I}{\partial x} \frac{\partial x}{\partial t} + \frac{\partial I}{\partial y} \frac{\partial y}{\partial t} + \frac{\partial I}{\partial t} = 0 </math> | ||
==Sensor fusion== | ==Sensor fusion== | ||
Revision as of 12:08, 26 May 2018
IMU
Lidar
Optical flow
Optical flow refers to estimation of apparent velocities of certain objects in an image. This is done by measuring the optical flow of each frame using which velocities of objects can be estimated. It is 2D vector field where each vector is a displacement vector showing the movement of points from first frame to second. By estimating the flow of points in a frame, the velocity of the moving camera can be calculated.
Working Principle
If [math]\displaystyle{ I(x,y,t) }[/math] is a pixel in an image then after some time [math]\displaystyle{ dt }[/math], as the pixel moves some distance [math]\displaystyle{ dx }[/math] and [math]\displaystyle{ dy }[/math] then as the pixel intensity is consistent, it can be said that;
[math]\displaystyle{ I(x,y,t) = I(x+dx, y+dy, t+dt) }[/math]
Using taylor series, it is possible to write
[math]\displaystyle{ \frac{\partial I}{\partial x} \frac{\partial x}{\partial t} + \frac{\partial I}{\partial y} \frac{\partial y}{\partial t} + \frac{\partial I}{\partial t} = 0 }[/math]