Enhancement of Object Tracking Accuracy in Low-Contrast Scenes

[yihong1120]

Dear motpy Maintainers,

I hope this message finds you well. I am reaching out to discuss a potential enhancement to the motpy library that could significantly improve tracking accuracy in low-contrast environments.

Context:
Upon utilising motpy for a project involving surveillance footage, I observed that the tracking accuracy diminishes notably in scenes where the contrast between the objects and the background is minimal. This is particularly evident during dusk and dawn sequences, where the lack of sufficient lighting conditions leads to poor object detection and subsequent tracking failures.

Suggestion:
I propose the introduction of a contrast enhancement pre-processing step before the detection phase. This could involve dynamic histogram equalisation or adaptive histogram equalisation (CLAHE) to improve the visibility of objects. An additional configuration parameter could allow users to enable or disable this feature based on their specific use case.

Potential Benefits:

• Improved detection and tracking in challenging lighting conditions.
• Enhanced robustness of the motpy library across a wider range of scenarios.
• Greater utility for users dealing with consistently low-contrast footage.

Preliminary Results:
I have conducted preliminary experiments by manually applying CLAHE to the input frames before feeding them into the motpy tracker. The initial results are promising, showing a marked improvement in tracking consistency.

Conclusion:
I believe this enhancement could be a valuable addition to the motpy library. I am more than willing to contribute to the development of this feature and provide further details on my findings. Your thoughts on this suggestion would be greatly appreciated.

Thank you for your time and consideration.

Best regards,
yihong1120