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Photogrammetry is an estimative scientific method that aims at recovering the exact positions and motion pathways of designated reference points located on any moving object, on its components and in the immediately adjacent environment. Photogrammetry employs high-speed imaging and the accurate methods of remote sensing in order to detect, measure and record complex 2-D and 3-D motion fields (see also SONAR, RADAR, LiDAR etc.). Photogrammetry feeds the measurements from remote sensing and the results of imagery analysis into computational models in an attempt to successively estimate, with increasing accuracy, the actual, 3-D relative motions within the researched field.
Its applications include satellite tracking of the relative positioning alterations in all Earth environments (e.g. tectonic motions etc), the research on the swimming of fish, of bird or insect flight, other relative motion processes (International Society for Photogrammetry and Remote Sensing). The quantitative results of photogrammetry are then used to guide and match the results of computational models of the natural systems, thus helping to invalidate or confirm new theories, to design novel vehicles or new methods for predicting or/and controlling the consequences of earthquakes, tsunamis, any other weather types, or used to understand the flow of fluids next to solid structures and many other processes.
Photogrammetry is as old as modern photography, can be dated to the mid-nineteenth century, and its detection component has been emerging from radiolocation, multilateration and radiometry while its 3-D positioning estimative component (based on modeling) employs methods related to triangulation, trilateration and multidimensional scaling.
In the simplest example, the distance between two points that lie on a plane parallel to the photographic image plane can be determined by measuring their distance on the image, if the scale (s) of the image is known. This is done by multiplying the measured distance by 1/s.
Algorithms for photogrammetry typically attempt to minimize the sum of the squares of errors over the coordinates and relative displacements of the reference points. This minimization is known as bundle adjustment and is often performed using the Levenberg–Marquardt algorithm.
Photogrammetry uses methods from many disciplines, including optics and projective geometry. The data model on the right shows what type of information can go into and come out of photogrammetric methods.
The 3-D co-ordinates define the locations of object points in the 3-D space. The image co-ordinates define the locations of the object points' images on the film or an electronic imaging device. The exterior orientation of a camera defines its location in space and its view direction. The inner orientation defines the geometric parameters of the imaging process. This is primarily the focal length of the lens, but can also include the description of lens distortions. Further additional observations play an important role: With scale bars, basically a known distance of two points in space, or known fix points, the connection to the basic measuring units is created.
Each of the four main variables can be an input or an output of a photogrammetric method.
Photogrammetry has been defined by the American Society for Photogrammetry and Remote Sensing (ASPRS) as the art, science, and technology of obtaining reliable information about physical objects and the environment through processes of recording, measuring and interpreting photographic images and patterns of recorded radiant electromagnetic energy and other phenomena.
Photogrammetric data with a dense range data in which scanners complement each other. Photogrammetry is more accurate in the x and y direction while range data are generally more accurate in the z direction. This range data can be supplied by techniques like LiDAR, laser scanners (using time of flight, triangulation or interferometry), white-light digitizers and any other technique that scans an area and returns x, y, z coordinates for multiple discrete points (commonly called "point clouds"). Photos can clearly define the edges of buildings when the point cloud footprint can not. It is beneficial to incorporate the advantages of both systems and integrate them to create a better product.
A 3-D visualization can be created by georeferencing the aerial photos and LiDAR data in the same reference frame, orthorectifying the aerial photos, and then draping the orthorectified images on top of the LiDAR grid. It is also possible to create digital terrain models and thus 3-D visualisations using pairs (or multiples) of aerial photographs or satellite (e.g. SPOT satellite imagery). Techniques such as adaptive least squares stereo matching are then used to produce a dense array of correspondences which are transformed through a camera model to produce a dense array of x, y, z data which can be used to produce digital terrain model and orthoimage products. Systems which use these techniques, e.g. the ITG system, were developed in the 1980s and 1990s but have since been supplanted by LiDAR and radar-based approaches, although these techniques may still be useful in deriving elevation models from old aerial photographs or satellite images.
Photogrammetry is used in different fields, such as topographic mapping, architecture, engineering, manufacturing, quality control, police investigation, and geology, as well as by archaeologists to quickly produce plans of large or complex sites and by meteorologists as a way to determine the actual wind speed of a tornado where objective weather data cannot be obtained. It is also used to combine live action with computer-generated imagery in movie post-production; The Matrix is a good example of the use of photogrammetry in film (details are given in the DVD extras).
This method is commonly employed in collision engineering, especially with automobiles. When litigation for accidents occurs and engineers need to determine the exact deformation present in the vehicle, it is common for several years to have passed and the only evidence that remains is accident scene photographs taken by the police. Photogrammetry is used to determine how much the car in question was deformed, which relates to the amount of energy required to produce that deformation. The energy can then be used to determine important information about the crash (such as the velocity at time of impact).
A more sophisticated technique, called stereophotogrammetry, involves estimating the three-dimensional coordinates of points on an object. These are determined by measurements made in two or more photographic images taken from different positions (see stereoscopy). Common points are identified on each image. A line of sight (or ray) can be constructed from the camera location to the point on the object. It is the intersection of these rays (triangulation) that determines the three-dimensional location of the point. More sophisticated algorithms can exploit other information about the scene that is known a priori, for example symmetries, in some cases allowing reconstructions of 3-D coordinates from only one camera position.
|It has been suggested that this section be split into a new article titled Comparison of Photogrammetry Software. (Discuss) Proposed since December 2013.|
|Platform||Standalone / Plugin||Automatic modelling||Scalability||Data source||Inception||Vendor / creator||Guide price|
|3DF Zephyr||Microsoft Windows||Standalone||Yes||Yes, multiple images||Images||2013||3DFLOW||$2900|
|Australis||Microsoft Windows||Standalone||Yes||Yes, multiple images||Images||1997||Photometrix||US$10100|
|EnsoMOSAIC||Microsoft Windows||Standalone||Yes||Yes, multiple images||Images||1995||MosaicMill||$900|
|PC-Rect||Microsoft Windows||Standalone||Yes||Yes, video||Images||1993||DSD[disambiguation needed]||€1200–1700|
|VI3DIM||Microsoft Windows||Standalone||Yes||Yes, video||video||2010||Vi3Dim||$20–395|
|SMART3DCAPTURE||Unknown||Standalone||Yes||Yes, multiple images||Images||2011||ACUTE3D||Unknown|
|ARC3D||Web-based||Standalone||Yes||Yes, multiple images||Images||2005||KU Leuven||Free|
|Pixdim||Unknown||Plugin||Yes||Yes, 1, 2 and multiple images||Images||Unknown||Qualup SAS||$1100|
|RhinoPhoto||Unknown||Plugin||Yes||Yes, multiple images||Images||Unknown||Qualup SAS||$1100|
|PhotoSculpt||Unknown||Standalone||Yes||No, 2 images only||Images||Unknown||Hippolyte Mounier||$99|
|iWitness / iWitnessPRO||Microsoft Windows||Standalone||Yes||Yes, multiple images||Images||2003||Photometrix||$995-$1995|
|PhotoModeler||Unknown||Standalone||Yes||Yes, multiple images||Images||1994||Eos Systems||$1145|
|4e Software||Unknown||Standalone||Yes||Yes, multiple images||Images||2012||4e Software||$1000|
|ImageModeler||Unknown||Standalone||No||Yes, multiple images||Images||2009||Autodesk||Subscription benefit|
|Match Photo||See SketchUp||Plugin/feature (SketchUp)||No||Yes, multiple images||Images||Unknown||Trimble Navigation||Unknown|
|PhotoSketch||Unknown||Unknown||Unknown||Unknown||Unknown||Unknown||Brainstorm Technology LLC||$350|
|3D pup-up||Unknown||Standalone||No||No, single image only||Image||2005||Carnegie Mellon University||non commercial|
|Yodel||Unknown||Standalone||Limited||Yes, multiple images||Images||2011||Lidar Pacific Corporation||$499|
|VideoTrace||Unknown||Tethered Beta||No||Yes, multiple images||Images/Video||2011||Australian Center for Visual Technology (AVCT), PunchCard||Beta Tester Only|
|123D Catch (Beta)||Web-based||Standalone||Yes||Yes, multiple images||Images/Video||2011||Autodesk||Free download|
|Hypr3D||Web-based||Standalone||Yes||Yes, multiple images||Images/Video||2010||Viztu Technologies||Free|
|ELCOVISION 10||Unknown||Standalone/Plugin||Yes||Yes, multiple images||Images||1986||PMS AG, Leica Geosystems||2000|
|PhotoScan||Unknown||Standalone/Plugin||Semi-automatic||Yes, multiple images||Images||2010||Ocali, Inc.||$999|
|PhotoScan||Microsoft Windows & MacOS & Linux||Standalone||Yes||Yes, multiple images||Images||2010||Agisoft||$179–3499 educational $59–549|
|DroneMapper||Web-based||Standalone||Yes||Yes, multiple images||Aerial Images||2012||DroneMapper||$20 per km2|
|StereoScan||Unknown||Standalone||Yes||No, 2 images only||Images||2010||Agisoft||Free|
|My3DScanner||Web-based||Standalone||Yes||Yes, multiple images||Images||2010?||My3DScanner||Free|
|PHOV||Web-based||Standalone||Yes||Yes, multiple images||Images||2010||XLAB||Free|
|Enwaii||Microsoft Windows/Linux/OS X||Standalone/Plugin (Maya)||No||Yes, multiple images||Images/Video/LIDAR||2008||Banzai Pipeline Ltd||Unknown|
|Mementify||iOS||Standalone||Yes||Yes, multiple images||Images||2012||Tretja dimenzija, XLAB||Free|
|WebDLT||Unknown||Standalone||No||Yes, multiple images||Images||2012||B. Molnar, BME FMT||Free|
|Trimble Business Center||Microsoft Windows||Standalone||Yes||Yes, multiple images||Images||2012||Trimble NV||Unknown|
|Pix4UAV||Microsoft Windows & Web-based||Standalone||Yes||Yes, multiple images||Images||2011||Pix4D SA||Unknown|
|Correlator3D||Microsoft Windows||Standalone||Yes||Yes, multiple images||Images||2003||SimActive Inc.||Unknown|
|VisualSFM||Microsoft Windows/Linux/OS X||Standalone||Yes||Yes, multiple images||Images||Unknown||Changchang Wu||Free|
|Scannerkiller||Microsoft Windows (64 Bit)||Standalone||No||Yes, multiple-pod config||Images||2004||XYZ RGB Inc.||$600–12,000|
|Ames Stereo Pipeline||Linux/OS X||Standalone||Yes||No, 2 images only||Images||Unknown||NASA||Free|
|uSMART||Microsoft Windows||Plugin (Bentley MicroStation)||Yes||Yes||Images||2000||uSMART||Unknown|
|Python Photogrammetry Toolbox||Microsoft Windows/Linux/OS X||Standalone||Yes||Yes, multiple images||Images||Unknown||Arc-Team||Free|
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