config_tracker_NvDCF_accuracy.yml

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BaseConfig:
  minDetectorConfidence: 0   # If the confidence of a detector bbox is lower than this, then it won't be considered for tracking

TargetManagement:
  enableBboxUnClipping: 1   # In case the bbox is likely to be clipped by image border, unclip bbox
  maxTargetsPerStream: 150  # Max number of targets to track per stream. Recommended to set >10. Note: this value should account for the targets being tracked in shadow mode as well. Max value depends on the GPU memory capacity

  # [Creation & Termination Policy]
  minIouDiff4NewTarget: 0.5   # If the IOU between the newly detected object and any of the existing targets is higher than this threshold, this newly detected object will be discarded.
  minTrackerConfidence: 0.2   # If the confidence of an object tracker is lower than this on the fly, then it will be tracked in shadow mode. Valid Range: [0.0, 1.0]
  probationAge: 3 # If the target's age exceeds this, the target will be considered to be valid.
  maxShadowTrackingAge: 150   # Max length of shadow tracking. If the shadowTrackingAge exceeds this limit, the tracker will be terminated.
  earlyTerminationAge: 1      # If the shadowTrackingAge reaches this threshold while in TENTATIVE period, the target will be terminated prematurely.

TrajectoryManagement:
  useUniqueID: 0   # Use 64-bit long Unique ID when assignining tracker ID.
  enableReAssoc: 1    # Enable Re-Assoc

  # [Re-Assoc: Motion-based]
  minTrajectoryLength4Projection: 20  # min trajectory length required to make projected trajectory
  prepLength4TrajectoryProjection: 10  # the length of the trajectory during which the state estimator is updated to make projections
  trajectoryProjectionLength: 90  # the length of the projected trajectory

  # [Re-Assoc: Trajectory Similarity]
  minTrackletMatchingScore: 0.5   # min tracklet similarity score for matching
  maxAngle4TrackletMatching: 30   # max angle difference for tracklet matching [degree]
  minSpeedSimilarity4TrackletMatching: 0.2 # min speed similarity for tracklet matching
  minBboxSizeSimilarity4TrackletMatching: 0.6 # min bbox size similarity for tracklet matching
  maxTrackletMatchingTimeSearchRange: 20      # the search space in time for max tracklet similarity

DataAssociator:
  dataAssociatorType: 0 # the type of data associator among { DEFAULT= 0 }
  associationMatcherType: 0 # the type of matching algorithm among { GREEDY=0, GLOBAL=1 }
  checkClassMatch: 1  # If checked, only the same-class objects are associated with each other. Default: true

  # [Association Metric: Thresholds for valid candidates]
  minMatchingScore4Overall: 0.0   # Min total score
  minMatchingScore4SizeSimilarity: 0.5  # Min bbox size similarity score
  minMatchingScore4Iou: 0.3       # Min IOU score
  minMatchingScore4VisualSimilarity: 0.6  # Min visual similarity score

  # [Association Metric: Weights]
  matchingScoreWeight4VisualSimilarity: 0.5  # Weight for the visual similarity (in terms of correlation response ratio)
  matchingScoreWeight4SizeSimilarity: 0.0    # Weight for the Size-similarity score
  matchingScoreWeight4Iou: 0.1   # Weight for the IOU score

StateEstimator:
  stateEstimatorType: 1  # the type of state estimator among { DUMMY=0, SIMPLE=1, REGULAR=2 }

  # [Dynamics Modeling]
  processNoiseVar4Loc: 2.0    # Process noise variance for bbox center
  processNoiseVar4Size: 1.0   # Process noise variance for bbox size
  processNoiseVar4Vel: 0.1    # Process noise variance for velocity
  measurementNoiseVar4Detector: 2.0    # Measurement noise variance for detector's detection
  measurementNoiseVar4Tracker: 10.0    # Measurement noise variance for tracker's localization

VisualTracker:
  visualTrackerType: 1 # the type of visual tracker among { DUMMY=0, NvDCF=1 }

  # [NvDCF: Feature Extraction]
  useColorNames: 1     # Use ColorNames feature
  useHog: 1            # Use Histogram-of-Oriented-Gradient (HOG) feature
  featureImgSizeLevel: 3  # Size of a feature image. Valid range: {1, 2, 3, 4, 5}, from the smallest to the largest
  featureFocusOffsetFactor_y: -0.2 # The offset for the center of hanning window relative to the feature height. The center of hanning window would move by (featureFocusOffsetFactor_y*featureMatSize.height) in vertical direction

  # [NvDCF: Correlation Filter]
  filterLr: 0.075 # learning rate for DCF filter in exponential moving average. Valid Range: [0.0, 1.0]
  filterChannelWeightsLr: 0.1 # learning rate for the channel weights among feature channels. Valid Range: [0.0, 1.0]
  gaussianSigma: 0.75 # Standard deviation for Gaussian for desired response when creating DCF filter [pixels]