interpolation for trajectories

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Interpolation for Trajectories Marc van Kreveld (UU) reporting on master thesis research of Bart Liefers (UU) also in collaboration with Emiel van Loon (UvA)

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Interpolation for Trajectories. Marc van Kreveld (UU) reporting on master thesis research of Bart Liefers (UU) also in collaboration with Emiel van Loon (UvA). Sampling and trajectories. Usually we get movement data from a set of measured locations at known times. (x 3 ,y 3 ), t 3. - PowerPoint PPT Presentation

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Page 1: Interpolation for Trajectories

Interpolation for Trajectories

Marc van Kreveld (UU)

reporting on master thesis research of Bart Liefers (UU)

also in collaboration with

Emiel van Loon (UvA)

Page 2: Interpolation for Trajectories

Sampling and trajectories

• Usually we get movement data from a set of measured locations at known times

(x1,y1), t1 (x2,y2), t2

(x3,y3), t3

(x3,y3), t3

Page 3: Interpolation for Trajectories

Sampling and trajectories

• Usually we get movement data from a set of measured locations at known times

(x1,y1), t1 (x2,y2), t2

(x3,y3), t3

(x3,y3), t3

(piecewise) linear interpolation

at time (t3+t2) /2

Page 4: Interpolation for Trajectories

Sampling and trajectories

• Sometimes linear interpolation is not called for

Page 5: Interpolation for Trajectories

Sampling and trajectories

• Sometimes linear interpolation is not called for

Page 6: Interpolation for Trajectories

Sampling and trajectories

• Interpolated location implies velocity (speed and heading)

(x1,y1), t1 (x2,y2), t2

(x3,y3), t3

(x3,y3), t3

linear interpolation constant speed

at time (t3+t2) /2

Page 7: Interpolation for Trajectories

The case of gulls

• Lesser black-backed gull

• Five gulls, colony on Texel• Sampling intervals irregular;

3 sec – 30 min• Also velocity measurements

Data from the UvA, computational geo-ecology,with Emiel van Loon and Judy Shamoun-Baranes

Page 8: Interpolation for Trajectories

30 measurements5:22 hours

Page 9: Interpolation for Trajectories

Interpolation affects basic properties

• Location at any time• Speed at any time• Trajectory length• Average speed

piecewise linear interpolation

spline interpolation

Page 10: Interpolation for Trajectories

Interpolation affects basic properties

• Location at any time• Speed at any time• Trajectory length• Average speed

• Availability of velocityallows new interpolations

piecewise linear interpolation

spline interpolation

Page 11: Interpolation for Trajectories

Interpolation affects basic properties

• Location at any time• Speed at any time• Trajectory length• Average speed

• Availability of velocityallows new interpolations

piecewise linear interpolation

spline interpolation

consistent spline interpolation

Page 12: Interpolation for Trajectories

Interpolation issues

• Consistency location and velocity:– Position correct at the measured locations– Velocity correct at the measured locations– Integral of velocity = path between any two

measured locations

• Scale-invariance for trajectory length:– fewer sampled locations should not result in a

smaller trajectory length

Page 13: Interpolation for Trajectories

Interpolation issues: gull specific

11:00, velocity 12 m/s 11:10, velocity 0 m/s

What velocity at 11:05?

Page 14: Interpolation for Trajectories

What probably happened between 11:00 and 11:10 …

Page 15: Interpolation for Trajectories

Interpolation issues: gull specific

• Speed constancy between measurements

12 m/s 1 m/s

t0 t1

t0 t1

speed profile

speed

time

Page 16: Interpolation for Trajectories

Interpolation issues: gull specific

• Speed constancy between measurements

12 m/s 1 m/s

t0 t1

t0 t1

speed profile

speed

time

Page 17: Interpolation for Trajectories

Interpolation models

• Linear model (basic, ignores velocity)• Cubic Bezier models

– Use measured velocity– Infer velocity from adjacent samples

• Speed constancy models– Linear interpolation for path (ignores heading)– Piecewise linear interpolation for path– Path from interpolation of heading

Page 18: Interpolation for Trajectories

Interpolation models

• Extrapolation model (use velocity of nearest sample, location is not continuous)

• Brownian bridges model

half-time

Page 19: Interpolation for Trajectories
Page 20: Interpolation for Trajectories

Properties of the models

linearcubic Bezier measured

cubic Bezier inferredspeed constancy, linear

speed constancy, PLspeed constancy, heading

extrapolationBrownian bridges

continuity

C0

C1

C1

C0

C0

C1

C-1

C0

speed

-yes

-yesyesyesyes

-

heading

-yes

--

yesyesyes

-

scale invariant

----

yes-

yes-

consistency

Page 21: Interpolation for Trajectories

Analysis using densely sampled trajectories

• Triples with 3-second intervals (exclude stationary birds)• Predict location & speed at middle sample from the

outer samples• Analyze coarser and coarser sampled trajectories

Page 22: Interpolation for Trajectories

Analysis using densely sampled trajectories

• Triples with 3-second intervals (exclude stationary birds)• Predict location & speed at middle sample from the

outer samples• Analyze coarser and coarser sampled trajectories

Linear model

Page 23: Interpolation for Trajectories

Analysis using densely sampled trajectories

• Triples with 3-second intervals (exclude stationary birds)• Predict location & speed at middle sample from the

outer samples• Analyze coarser and coarser sampled trajectories

Speed constancy model, linear

Page 24: Interpolation for Trajectories

Analysis using densely sampled trajectories

• Triples with 3-second intervals (exclude stationary birds)• Predict location & speed at middle sample from the

outer samples• Analyze coarser and coarser sampled trajectories

Cubic Bezier model using velocity

Page 25: Interpolation for Trajectories

Analysis of location

• At high resolution several models are best, about 20% better than linear interpolation

• At lower resolution the speed constancy model, linear, is best, about 30% better than linear interpolation

at lower resolutions, speed helps but heading doesn’t

Page 26: Interpolation for Trajectories

Analysis of speed and heading

• At high resolutions, several models are best for speed, including linear interpolation

• At lower resolutions the speed constancy model, linear, is best for speed

• For heading, linear interpolation is best, especially for lower resolutions

Page 27: Interpolation for Trajectories

Analysis of trajectory length

• The extrapolation model and piecewise linear speed constancy model are not biased by sampling rate, unlike all other models

• Simple integration of speed works best

Page 28: Interpolation for Trajectories

Conclusions

• For interpolation, scale matters• The particular application matters

• At lower resolutions, speed helps but heading doesn’t• Speed consistency models appear to work well for

location and velocity

Page 29: Interpolation for Trajectories

The end