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Week 1. Metrics and tools for background subtraction / OF evaluation

Task 1. Background substraction. Segmentation metrics. Precision and recall.

  • Run the function evaluateFolder() in main.py
  • See the implementation of evaluateFolder() in evaluation.py

Task 2. Background susbtraction. Segmentation metrics. Temporal analysis.

  • Run the function evaluateTemporal() in main.py
  • See the implementation of evaluateTemporal() in evaluation.py

Task 3. Optical flow evaluation metrics. Mean Squared Error and Percentage of Erroneous Pixels in Non-occluded areas.

  • Run the function evaluateOpticalFlow() in main.py
  • See the implementation of evaluateOpticalFlow() in optical_flow.py

Task 4. Background substraction. Evaluation of de-synchornized results.

  • Run the function dSyncGlobalEvaluation() in main.py to check evolution of overall F1 over de-sync frames
  • Run the function dSyncTemporalEvaluation() in main.py to check evolution of F1 per frame over de-sync frames
  • See the implementation of dSyncGlobalEvaluation() and dSyncTemporalEvaluation() in evaualtion.py

Task 5. Visual representation of optical flow.

  • Run the function plotOpticalFlowHSV() in main.py
  • See the implementation details of plotOpticalFlowHSV() in optical_flow.py