[Concept] : [Atlas] : Bezier curves

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Core Concept/Theory A clear and concise description of what the concept is. Ex. It would be cool if [...]

Extend out the Bezier curves for the mouse movement within the Atlas module.

This will help us create better mouse movement, aiming to be more "human"-like, we will keep this part of the code just for the mouse movement algorithm and biohash data.

The idea is to capture mouse movements and translate these into Bezier curves using Python's mathematical capabilities. This approach not only allows for the graphical representation of mouse trajectories but also integrates a unique "BioHash" generated from these movements. The BioHash represents the human element, capturing the uniqueness of each user's interaction pattern. This can be useful for a variety of applications, including but not limited to, user authentication, artistic expression, or user behavior analysis.

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Alternative Ideas Is there any other way this concept could be used?

We can use this library for multiple applications, just having one source of truth for the mouse algos will be easier.

• The concept could be extended to touchpad gestures or mobile device interactions, capturing more diverse forms of human input.

• Beyond user authentication, the generated BioHash could be used for personalized user experiences, adjusting interfaces or recommendations based on the user's unique interaction patterns.

• This approach could also be used in digital art installations, where participants' movements directly influence the creation of dynamic, interactive art pieces.

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Alternative Examples/Sources Are there any other references that you can provide?

There are a couple of examples, including WindMouse by Benland and Ghost Mouse, but for the most part, the curves will be the hardest part.

• TODO: Research papers or articles on Bezier curves and their mathematical properties, to deepen understanding of curve generation based on input points.

• TODO: Studies or implementations of biometric hashing techniques, especially those focusing on behavioral biometrics, to explore how mouse movements can be effectively translated into a secure, unique hash.

• TODO: Examples of Python libraries or frameworks that facilitate the drawing of Bezier curves or the capture of mouse movements, such as matplotlib for curve plotting or pyautogui for mouse tracking.

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Additional information Add any other context or examples of this concept here.

• Exploration of the mathematical model behind Bezier curves, ensuring an accurate and efficient implementation in Python for real-time mouse movement capture.

• Consideration of privacy and security aspects when generating and storing BioHashes, especially if used for authentication or personalization purposes.

• Discussion on the granularity of mouse movement data required to generate a meaningful BioHash, balancing the need for uniqueness with computational efficiency and user privacy.

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Mouse Movement Library -> https://github.com/riflosnake/HumanCursor

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I am going to remove these from the library directly, as they are causing way too many errors!

I believe the best option would be to call this directly via the application.

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We can close this out as we were able to get the mouse movements that we like!

Next update will be either its own issue ticket or placed directly into the project's documentation.