We can make 3D shapes from photos. 

We can make 3D shapes from photos. 

Photogrammetry is a way to learn about objects using photos. 

One way to do this is called stereophotogrammetry. This uses two or more photos from different spots. By looking at where lines of sight meet, we find a point's exact place. This is called triangulation. It is like how your two eyes help you see depth.
People use this science in many ways. Filmmakers use it to make movies look real. Video game makers use it to build worlds. Archaeologists use it to map old sites. It even helps meteorologists find wind speeds in tornadoes. Experts use it to check things deep under the sea. They can study wind turbine bases or underwater cables. Even Google Earth uses it to make 3D views of our world.
Photogrammetry is a fascinating science used to learn about our world. 

How does this science actually work? One method is called stereophotogrammetry, which uses two or more photos. These pictures must be taken from different positions. Scientists find common points that appear in every single image. They then draw a line of sight, or a ray, from the camera to the object. Where these rays meet is called triangulation. This is the exact spot where the 3D location is found. It is a clever way to find depth using only light.
People have been working on this for a long time. The invention of this method is credited to Aimé Laussedat. Later, a German architect named Albrecht Meydenbauer created the name. He used the term "photogrammetry" in an article from 1867. 
There are many amazing ways to use these tools today. In movies, it helps blend real actors with computer images. 
You might have even seen photogrammetry in your own life. Google Earth uses it to create its 3D views of the world. 
Photogrammetry is a specialized science and technology used to obtain reliable information about physical objects and environments. 

The process involves several complex stages of digital image capturing and processing. To build a model, scientists must account for four main variables. First, they define the 3D coordinates, which are the specific locations of object points in space. Second, they identify image coordinates, which are the locations of those points on a film or electronic sensor. Third, they must establish the exterior orientation of the camera, which includes its position and view direction. Finally, they define the inner orientation, which involves the lens's focal length and any lens distortions.
To ensure these measurements are accurate, researchers use specific mathematical methods. One common technique is called stereophotogrammetry. This method estimates 3D coordinates by using two or more photographic images taken from different positions. Scientists identify common points that appear in every image. They then construct a line of sight, or a ray, from the camera location to the object point. The intersection of these rays is a process called triangulation. This intersection determines the exact three-dimensional location of the point.
Advanced algorithms help refine these models by minimizing errors. A common process is called bundle adjustment, which reduces the sum of the squares of errors across coordinates. This is often performed using the Levenberg–Marquardt algorithm. Researchers can also combine photogrammetry with other range data to improve accuracy. While photogrammetry is very accurate in the x and y directions, other tools like LiDAR are often more accurate in the z direction, or depth. By integrating these "point clouds" of data, scientists can create highly detailed 3D visualizations. 
The history of this field shows how much our tools have evolved. The invention of the method is attributed to Aimé Laussedat. However, the specific term "photogrammetry" was coined by the German architect Albrecht Meydenbauer. He introduced the name in his 1867 article, "Die Photometrographie." In the early days, workers used stereoplotters to draw contour lines on topographic maps. Today, the field has expanded to include high-speed photography, remote sensing, and drone technology. These advancements allow us to measure complex 2D and 3D motion fields with increasing precision.
Photogrammetry has a massive range of practical applications across many industries. In filmmaking, it is used to combine live action with computer-generated imagery, as seen in the movie *The Matrix*. Video game developers also use it to create photorealistic environments, such as in *Star Wars Battlefront*. Archaeologists use it to map complex excavation sites or to study ancient Graeco-Roman funerary masks. Even meteorologists use this science to determine the wind speed of tornadoes when other weather data is unavailable. 
In engineering and environmental science, the data is vital for safety and monitoring. Collision engineers use old police photographs to determine how much a vehicle was deformed in a crash. This helps them calculate the energy and velocity involved in the impact. In the marine sector, subsea photogrammetry allows for the inspection of offshore wind turbine foundations and underwater cables. It is also used to track environmental changes. For example, on Mount Stanley, drone photography and GNSS technology showed that a glacier's surface area declined by 29.5% between 2020 and 2024. 
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