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Parameters: |
Step 1: Detection |
Gaussian Mixture-Model Fitting |
Gaussian Standard Deviation = 1.7 pixels |
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Camera Bit Depth: 16 |
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Local Maxima Detection: |
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Alpha-value for Comparison with Local Background = 0.05 |
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Do Not Check “Use Rolling Window Time-Averaging” |
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Do Not Check “Use Absolute Background” |
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Gaussian Fitting at Local Maxima: |
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Check “Iterate to Estimate Gaussian Standard Deviation” |
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Maximum Number of Iterations = 10 |
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Check “Do Iterative Gaussian Mixture-Model Fitting” |
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Alpha values: |
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Residuals = 0.05 Distance = 0.05 |
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Amplitude = 0.05 Final = 0 |
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Input and Output: |
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Frames to Use = 1–100 for Population or 1–250 for Residence |
Step 2: Tracking |
Tracking Parameters |
Parameters: |
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Problem Dimensionality = 2 |
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Maximum Gap to Close = 5 Frames for Population or 1 Frames for Residence |
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Maximum Length of Track Segments from First Step = 1 Frame |
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Check “Do segment merging” |
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Check “Do segment splitting” |
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Do Not Check “ Plot histogram of gap lengths after gap closing” |
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Check “Show calculation progress in command line” |
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Do Not Check “Export tracking result to matrix format” |
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Cost Functions: |
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Step 1: frame-to-frame linking: |
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Check “Allow direct motion position propagation” |
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Check “Allow instantaneous direction reversal” |
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Brownian Search Radius (in pixels): |
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Lower Bound = 1 |
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Upper Bound = 20 for Population or 10 for Residence |
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Multiplication Factor for Brownian Search Radius Calculation = 3 |
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Check “Use nearest neighbor distance to expand Brownian search radius” |
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Number of Frames for Nearest Neighbor Distance Calculation = 20 for Population or 10 for Residence. |
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Do Not Check “Plot histogram of linking distances” |
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Step 2: gap closing, merging and splitting: |
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Brownian + Directed motion models |
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Brownian Search Radius (in pixels): |
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Lower Bound = 1 |
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Upper Bound = 20 for Population or 10 for Residence |
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Multiplication Factor for Brownian Search Radius Calculation = 3 |
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Check “Use nearest neighbor distance to expand Brownian search radius” |
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Number of Frames for Nearest Neighbor Distance Calculation = 20 for Population and 10 for Residence |
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How to expand the Brownian search radius with gap length: |
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Scaling Power in Fast Expansion Phase = 0.5 |
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Scaling Power in slow Expansion Phase = 0.01 |
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Gap length to transition from Fast to Slow Expansion = 5 for Population or 1 for Residence |
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Penalty for Increasing Gap Length = 1.5 |
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Check “In merging and splitting, consider ratio of intensities before and after merge/split: |
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Ratio of Intensity: Min Allowed = 0.5 Max Allowed = 2 |
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Leave it Blank “Value of search Radius Lower Bound for Merging/Splitting (in pixels) ” |
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Check “Allow direct motion position propagation” |
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Check “Allow instantaneous direction reversal” |
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Minimum Track Segment Lifetime for Classification as Linear or Random (in frames) = 5 |
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Multiplication Factor for Linear Search Radius Calculation = 3 |
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How to scale the linear motion search radius with time: |
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Scaling Power in Fast Expansion Phase = 0.5 |
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Scaling Power in Slow Expansion Phase = 0.01 |
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Gap length to transition from Fast to Slow Expansion = 5 for Population or 1 for Residence |
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Maximum Angle Between Linear Track Segments (in degree) = 30 |
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Kalman Filter Functions |
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Kalman functions = Brownian + Directed motion models |
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Parameters: |
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Do Not Check “Initial velocity estimate (in pixels/frame) ” |
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Do Not Check “Reference point for initial velocity estimate (in pixels) ” |
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Check “None of the two above” |
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Leave it Blank “Search Radius for first Iteration (in frames)” |