Optimize Background Subtraction Performance

[Blindspot22]

Description:

• Analyze and optimize the performance of the background subtraction algorithms to ensure they run efficiently in real-time.

Implementation Steps:

• Profile the performance of the MOG2 and KNN algorithms using tools like perf or valgrind to identify bottlenecks.
• Experiment with different parameter settings (e.g., history length, shadow detection) to find the optimal balance between accuracy and speed.
• Implement optimizations such as multi-threading or parallel processing to improve performance, especially for high-resolution video streams.
• Minimize memory usage by optimizing the handling of foreground masks and reducing unnecessary allocations.
• Document the performance benchmarks and provide guidelines on how to tune the parameters for different environments (e.g., indoor vs. outdoor).