Identify Key Parameters for Tuning

[Blindspot22]

Description:

• Identify and list the key parameters that significantly impact the performance and accuracy of the background subtraction, contour detection, and bounding box visualization algorithms.

Implementation Steps:

• Review the algorithms implemented for background subtraction (MOG2, KNN), contour detection, and bounding box visualization.
• Identify critical parameters such as history, threshold, detect_shadows, min_contour_area, and bounding box padding.
• Document each parameter, explaining its role, range of acceptable values, and how it influences the outcome.
• Group the parameters based on their association with specific components (e.g., background subtraction, contour detection).
• Create a baseline configuration file or structure in the code that holds default values for these parameters, which can be modified later.