Active Shape Model (ASM)
Active Shape Model (ASM) is a model-based methods, which makes use of a prior model of what is expected in the image, and typically attempt to find the best match position between the model and the data in a new image. One can make measurements whether the target is actually presented after matching the model. In face recognition application, we collect training images, represent all shapes with a set of landmarks, to form a Point Distribution Model (PDM) respectively.
After landmarks alignment and Principal Component Analysis, we construct gray-level profile for each landmark in all multi-resolution versions of a training image.
In search procedure, we give the model’s position an initial estimate. Then it can compute the suggested movements through an iteration approach using the gray-level profile. When convergence is established, we get a final matching result.
Example of image search
According to some disadvantages of ASM, we adopt a lot of improvements, such as increasing the width of search profile to reduce the effect of noise, grouping landmarks to avoid mouth shape distort in the search procedure and alter the direction of search profile.
Search result before and after using landmarks grouping