Learning AAM fitting through simulation

Learning AAM fitting through simulation

The Active Appearance Model (AAM) is a powerful method for modeling and segmenting deformable visual objects. The utility of the AAM stems from two fronts: its compact representation as a linear object class and its rapid fitting procedure, which utilizes fixed linear updates. Although the original fitting procedure works well for objects with restricted variability when initialization is close...

Surveying capsid assembly pathways through simulation-based data fitting.

Virus capsid assembly has attracted considerable interest from the biophysical modeling community as a model system for complicated self-assembly processes. Simulation methods have proven valuable for characterizing the space of possible kinetics and mechanisms of capsid assembly, but they have so far been able to say little about the assembly kinetics or pathways of any specific virus. It is n...

Adult learning through case simulation.

This article was accepted for publica/ion April 11, 1994 The body of knowledge in health care and its environmen( is rapidly changing, To remain viable as professionals, health care practitioners must stay curren( with practice changes, legislation trends, and technological advances, Information can be obtained through various avenues, such as in-services within the faCility, peer audit review,...

Statistical Learning of Evaluation Function for ASM/AAM Image Alignment

Alignment between the input and target objects has great impact on the performance of image analysis and recognition system, such as those for medical image and face recognition. Active Shape Models (ASM)[1] and Active Appearance Models (AAM) [2, 3] provide an important framework for this task. However, an effective method for the evaluation of ASM/AAM alignment results has been lacking. Withou...

Learning High-Energy Trauma Care Through Simulation