About the blog

Welcome to a focused learning space dedicated to photogrammetry and computational geometry.
This blog is built around a simple idea: complex technical concepts should be explained clearly, step by step, and with practical insight. The content here is inspired by structured academic material in photogrammetric computations, but presented in a way that is easier to follow, apply, and revisit.

🎯 Purpose
The goal of this blog is to help readers understand how geometric information can be extracted from images using mathematical models and computational techniques. Rather than staying purely theoretical, the posts aim to bridge the gap between theory and real-world implementation.
You will find explanations that focus on:
Breaking down complex formulas into understandable steps
Connecting mathematical concepts to real applications
Providing intuitive understanding alongside technical detail

📚 What You’ll Learn
This blog covers a wide range of topics in photogrammetry and related fields, including:
Fundamental concepts of photogrammetry
2D and 3D rotation systems (Euler angles, rotation matrices)
Coordinate transformations (conformal, affine, projective)
Camera models and image coordinate systems
Interior and exterior orientation
Relative and absolute orientation techniques
Core equations such as collinearity and coplanarity
Practical computational approaches and numerical methods
The content is structured progressively, so you can follow along from basic concepts to more advanced topics.

👨‍💻 Who This Is For
This blog is designed for:
Students in geomatics, surveying, or computer vision
Engineers and developers working with spatial data
Anyone interested in understanding how images can be turned into measurable 3D information
Whether you are learning for academic purposes or building real-world applications, the aim is to provide clear and useful knowledge.

⚙️ Approach
Some methods presented here prioritize clarity over computational efficiency. The intention is to build strong conceptual understanding first, which can later be optimized for performance in real applications.
Whenever possible, explanations may include:
Step-by-step derivations
Visual intuition
Practical examples

🚀 Vision
This blog is part of an ongoing effort to make photogrammetry more accessible. As the field continues to evolve—especially with advances in computer vision and machine learning—clear foundational understanding becomes even more important.
New content will continue to expand on both theory and implementation, helping readers move from learning concepts to applying them confidently.

If you’re interested in how images become data, models, and measurable reality—you’re in the right place.

Created by: Ehsan Khoramshahi

Dr. Ehsan Khoramshahi is a researcher and practitioner in the fields of photogrammetry, computer vision, and geospatial science. His work focuses on developing mathematical models and computational methods for extracting accurate spatial information from images, with particular emphasis on multi-view geometry, camera modeling, and real-time georeferencing systems.

Over the course of his academic and professional career, Dr. Khoramshahi has been involved in research and development projects related to UAV-based mapping, mobile mapping platforms, and image-based measurement systems. His contributions bridge theoretical photogrammetry and practical implementation, aiming to simplify complex concepts while maintaining mathematical rigor.

He is the author of the book Photogrammetric Computations, where he presents foundational principles of photogrammetry in a structured and accessible manner, combining analytical formulations with numerical approaches and implementation insights.

He is affiliated with University of Eastern Finland (UEF) and collaborates with academic and research institutions in Finland. His work reflects a continuous effort to make photogrammetric methods more understandable, practical, and applicable to modern imaging technologies.

Through this weblog, Dr. Khoramshahi shares insights, tutorials, and reflections on photogrammetry and computer vision, with the aim of supporting students, researchers, and professionals in the field.