In my research, we are keen on analyzing moving images to extract geometric objects and understand motion, which is crucial for applications like self-driving cars. Geometric algebra serves as a unifying language, simplifying complex computations in fields like computer vision, making it easier to work with concepts like rotations and translations without confusion.

Using geometric algebra provides a clear origin point for calculations, eliminating the confusion of multiple coordinate systems and making it easier to handle rotations and translations in computer vision.

Geometric algebra provides a mathematical framework that allows us to work with lines in computer vision, which is more complex than working with points.

The beauty of geometric algebra lies in its ability to represent complex geometric transformations intuitively, making programming and computation more straightforward.

I collaborated with a motion capture company to develop algorithms for camera calibration, leveraging the unique properties of geometric algebra to enhance the process.

The goal during my five-year research period was to apply geometric algebra to practical uses and basic research, exploring its potential in various applications.

Geometric algebra allows for a unified approach to various fields, enabling work in rigid body dynamics, linear algebra, and quantum physics without relying on matrices or tensors.

My husband, Anthony, became fascinated with geometric algebra, which led me to explore its applications in engineering, particularly in rotations.

The challenge in adopting geometric algebra lies in the established use of vector calculus and linear algebra, which makes it difficult for researchers to shift to this new mathematical system.