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Active shape models (ASMs) are
/ref> 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.
The ASM works by alternating the following steps:
* Generate a suggested shape by looking in the image around each point for a better position for the point. This is commonly done using what is called a "profile model", which looks for strong edges or uses the Mahalanobis distance to match a model template for the point.
* Conform the suggested shape to the point distribution model, commonly called a "shape model" in this context. The figure to the right shows an example.
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 an analog to an
Matlab code
open-source ASM implementation.
of AAMs from Manchester University.
Tim Cootes'
home page (one of the original co-inventors of ASMs).
Source code
for ASMs (the "stasm" library).
ASMlib-OpenCV
An open source C++/OpenCV implementation of ASM. {{DEFAULTSORT:Active Shape Model Computer vision
statistical model
A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from a larger population). A statistical model represents, often in considerably idealized form, ...
s of the shape
A shape or figure is a graphical representation of an object or its external boundary, outline, or external surface, as opposed to other properties such as color, texture, or material type.
A plane shape or plane figure is constrained to lie on ...
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./ref> 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.
The ASM works by alternating the following steps:
* Generate a suggested shape by looking in the image around each point for a better position for the point. This is commonly done using what is called a "profile model", which looks for strong edges or uses the Mahalanobis distance to match a model template for the point.
* Conform the suggested shape to the point distribution model, commonly called a "shape model" in this context. The figure to the right shows an example.
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 an analog to an active contour model Active contour model, also called snakes, is a framework in computer vision introduced by Michael Kass, Andrew Witkin, and Demetri Terzopoulos for delineating an object outline from a possibly noisy 2D image. The snakes model is popular in comput ...
which would respect explicit shape constraints.
See also
*Procrustes analysis
In statistics, Procrustes analysis is a form of statistical shape analysis used to analyse the distribution of a set of shapes. The name ''Procrustes'' ( el, Προκρούστης) refers to a bandit from Greek mythology who made his victims fit ...
* Point distribution model
References
External links
Matlab code
open-source ASM implementation.
of AAMs from Manchester University.
Tim Cootes'
home page (one of the original co-inventors of ASMs).
Source code
for ASMs (the "stasm" library).
ASMlib-OpenCV
An open source C++/OpenCV implementation of ASM. {{DEFAULTSORT:Active Shape Model Computer vision