Active shape model
Encyclopedia
Active shape models are statistical model
s of the shape
of objects which iteratively deform to fit to an example of the object in a new image, developed by Tim Cootes and Chris Taylor in 1995 . The shapes are constrained by the PDM (point distribution model
) Statistical Shape Model to vary only in ways seen in a training set of labelled examples.
The shape of an object is represented by a set of points (controlled by the shape model). The ASM algorithm aims to match the model to a new image. It works by alternating the following steps:
To locate a better position for each point one can look for strong edges, or a match to a statistical model of what is expected at the
point. The original methodology suggests using the Mahalanobis distance
to detect a better position for each landmark point .
The technique has been widely used to analyse images of faces, mechanical assemblies and medical images (in 2D and 3D).
It is closely related to the active appearance model
. It is also known as a “Smart Snakes” method, since it is analog to an active contour model which would respect explicit shape constraints.
Statistical model
A statistical model is a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or more random variables. The model is statistical as the variables are not deterministically but...
s of the shape
Shape
The shape of an object located in some space is a geometrical description of the part of that space occupied by the object, as determined by its external boundary – abstracting from location and orientation in space, size, and other properties such as colour, content, and material...
of objects which iteratively deform to fit to an example of the object in a new image, developed by Tim Cootes and Chris Taylor in 1995 . The shapes are constrained by the PDM (point distribution model
Point distribution model
The point distribution model is a model for representing the mean geometry of a shape and some statistical modes of geometric variation inferred from a training set of shapes.-Background:...
) Statistical Shape Model to vary only in ways seen in a training set of labelled examples.
The shape of an object is represented by a set of points (controlled by the shape model). The ASM algorithm aims to match the model to a new image. It works by alternating the following steps:
- Look in the image around each point for a better position for that point
- Update the model parameters to best match to these new found positions
To locate a better position for each point one can look for strong edges, or a match to a statistical model of what is expected at the
point. The original methodology suggests using the Mahalanobis distance
Mahalanobis distance
In statistics, Mahalanobis distance is a distance measure introduced by P. C. Mahalanobis in 1936. It is based on correlations between variables by which different patterns can be identified and analyzed. It gauges similarity of an unknown sample set to a known one. It differs from Euclidean...
to detect a better position for each landmark point .
The technique has been widely used to analyse images of faces, mechanical assemblies and medical images (in 2D and 3D).
It is closely related to the active appearance model
Active Appearance Model
An active appearance model is a computer vision algorithm for matching a statistical model of object shape and appearance to a new image. They are built during a training phase...
. It is also known as a “Smart Snakes” method, since it is analog to an active contour model which would respect explicit shape constraints.
External links
- Matlab code open-source ASM implementation.
- Description of AAMs from Manchester University.
- Tim Cootes' home page (one of the original co-inventors of ASMs).
- Source code for ASMs (the "stasm" library).