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Intoduction to Photogrammetry

Photogrammetry is both an art and a science focused on extracting meaningful information from images. This includes geometric measurements, radiometric properties, classification data, and even the uncertainties associated with them. At its core, photogrammetry transforms visual data into precise, measurable insights using advanced processing techniques and computational methods.
Images are the primary data source in photogrammetry and can be categorized based on their distance from the subject. These categories typically include spatial, aerial, and short-range imagery. However, modern photogrammetry is not limited to traditional images alone. It also incorporates diverse data types such as point clouds, radar measurements, laser scans, and multi- or hyperspectral imagery, all of which contribute to a richer and more comprehensive analysis.
The field is highly interdisciplinary, intersecting with several areas of science and technology. A solid understanding of statistics and probability is essential for interpreting uncertainties in measurements. Optimization techniques help estimate parameters efficiently, while image processing plays a crucial role in extracting features and generating point clouds. Additionally, machine learning and neural networks are increasingly used to identify patterns, and electronics support the design of measurement systems.
This work is the result of years of research and teaching in photogrammetry and computer vision. It is designed to simplify complex concepts and present them in an accessible manner, particularly for students. The material follows a structured approach—starting with fundamental principles and gradually introducing more advanced topics, along with partial implementation examples using programming tools such as Python.
Some of the methods presented are experimental and developed specifically for educational purposes. While they may not always represent the most computationally efficient solutions, they are intended to provide deeper conceptual understanding, which is a key objective of this work.
Photogrammetry continues to evolve as a field driven by collaboration and shared knowledge. Contributions from researchers and practitioners help refine methodologies and advance the discipline. This resource aims to support that ongoing development by offering a clear and approachable foundation for learners worldwide.

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You can find description to Euler Angles & Rotation Matrices here.