Errors and Mistakes in Automated Player Tracking

1
Errors and Mistakes in Automated PlayerTracking
2
Outline

• Introduction and motivation
• Sources and types of errors
• Tracking parameters
• Ground truth, experiments and results
• Conclusion

3
Introduction and motivation

• Automated player tracking system has been
  developed in our lab.

How accurate is it?
4
Introduction and motivation

• Related work
• 10 articles describing people/sport related
  tracking at ICPR 2000, Barcelona.
• 8 did not mention tracking accuracy 1
  proposed the accuracy measure 1 specified
  the accuracy (tracking the tennis ball)
• Research is focused mainly on reliability.
• Our motivation sport experts (end users).

5
Sources and types of errors

Note We track global movement of players for
the purpose of match analysis. No operator
mistakes are allowed.
6
Tracking parameters

• Tracking method used 3 available 2
  included in experiments
• Post-processing of trajectories filter
  width
• Position of the players radial distortion
  non-uniform quantization
• Activity of the players movement of
  extremities

7
Ground truth

• A reliable reference for player position was
  needed.
• Several patterns were drawn on the court,
  players were instructed to follow them.
• Patterns were measured using measuring tape.

8
Experiment I.

• Position accuracy (RMS error) and path length
  error with respect to
• different tracking methods player
  position player activity.

2 players at court boundary, 3 near court
center. 60 seconds (_at_25 fps) standing still,
150 seconds active (passing ball, jumping -
all at the same position).
9
Experiment I.

• 2D histograms of player position,cumulative
  histograms of absolute position error

RMS position error 0.18 - 0.50 m (still) 0.28 -
0.63 m (active) Path length error 0.6 - 1
m/player/min (still) 6 - 10 m/player/min (active)
Combined (color template tracking) method
performed better than background subtraction.
Wide FIR filter decreases error in path length -
heavy smoothing preferred.
10
Experiment II.

• Effect of FIR filter width (wide filter
  intense smoothing) to square trajectory.
• Error measure
• In presence of rapid changes in player
  direction, wide filter distorts trajectory.

11
Experiment III.

• Velocity accuracy (RMS error) for uniform
  player motion.
• Circular trajectory as ground truth, constant
  velocity of players assumed.
• Reference velocity calculated from trajectory
  length and the time player
• needed for one round.
• 5 players, Vref from 2.7 to 3.2 m/s
• RMS error of player velocity
• less smoothing 0.21 to 0.35 m/s (6-12)
• more smoothing 0.07 to 0.20 m/s (3-7)

12
Experiment IV.

• Velocity and position accuracy.
• APAS (manual video-based kinematic analysis
  tool) was used as a ground truth.
• Two short sequences only - motion analysis
  using APAS is time consuming.

RMS position error 0.28 m to 0.38 m RMS
velocity error 0.5 m/s to 0.7 m/s
13
Conclusion

• RMS position error from 0.2 m to 0.6 m
• RMS velocity error from 0.2 m/s to 0.4 m/s
• Path length error from 1 m to 10 m (per
  one player per minute)
• Players are large non-rigid objects - at
  this scale the limit is imposed by the
  definition of player position, velocity and
  path length itself.
• Ideas for future work above definitions and
  similar research concerning manual position
  measurements.