Tip 41: PhotoModeler’s Different Ways to Select Points

Another short and useful tip this week. This tip shows the different ways to select one or more points in the PhotoModeler interface. Point selection is a key operation for many tasks such as getting measurements, referencing, moving, deleting, and triangulating points, etc. Often you need to select groups of points and this tip video […]

Tip 40: PhotoModeler’s 3D Viewer Controls

We have a short video tip for you this week (less than a minute!).  This tip video points out a small feature that would normally be hard to find. That is, the use of the CTRL key to modify how view rotation works in PhotoModeler’s 3D Viewer. The video first reviews the standard ways of […]

Tip 37: Finding matching external geometry in PhotoModeler

In many photogrammetry projects you will use external knowledge to refine or add to the project. This external knowledge can be scale measurements, control points, survey data, CAD files, coordinate system definitions, point clouds, etc. Three common forms of external information are: a known distance between two points to define an accurate scale, points selected […]

PhotoModeler’s New Point Cloud Meshing Capabilities

A number of improvements were made to the meshing capabilities in PhotoModeler Scanner version 2013.0.1 (April 22, 2013). Meshing is a key component in Scanner when working with point clouds created by DSM or by importing (such as from a laser scanner). The meshing steps have been redesigned to streamline the process of creating a […]

Tip 36: PhotoModeler’s Automatic Camera Library Matching

PhotoModeler’s automatic camera matching is great for reducing errors and improving project start-up time when you work with more than one camera in your photogrammetry project. This tip video shows the various ways that camera matching works (with one or more cameras in a single project). Automated camera matching is done on photographs from most […]

Tip 34: Study Confidence Regions in PhotoModeler for Point Quality

  In many measurement tasks one needs to understand how well the positions of 3D points are known; or how confident one can be in their computed positions. Mathematically this confidence is defined by the point’s precision (or standard deviation). An estimate of photogrammetric precision is computed by PhotoModeler’s bundle adjustment algorithm when it solves […]

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