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Active shape model is widely used for facial feature localization. Regarding the traditional ASM algorithm can't describe the object shape precisely, an improved ASM algorithm is proposed. At first, we establish shape model and use PCA (Principle Component Analysis) to transform high-dimensional data to lower dimensions. Another work is to establish local texture model giving sample points with different...
Shape outliers can seriously affect the statistical analysis of the shape variations usually performed by the Principal Component Analysis PCA. This paper presents an algorithm for outliers detection and shape restoration as a new strategy for robust statistical shape analysis. The proposed framework is founded on an elastic metric in the shape space to cope with the nonlinear shape variability. The...
Statistical shape models (SSMs) are widely used for introducing shape priors in medical image analysis. However, building a SSM usually requires careful data acquisitions to gather training datasets with both sufficient quality and enough shape variations. We present a robust framework to build reliable SSMs from a dataset with outliers and incomplete data. Our method is based on Point Distribution...
Sources of uncertainty in the boundaries of structures in medical images have motivated the use of probabilistic labels in segmentation applications. An important component in many medical image segmentation tasks is the use of a shape model, often generated by applying statistical techniques to training data. Standard statistical techniques (e.g., principal component analysis) often assume data lies...
This paper addresses the generic object counting problem with object overlapping occurring at varied levels and degrees. The overall image containing the objects is segmented from the background. Thereafter a combination of parameters is extracted from each of the segments to construct a parameter space. The overall space formed by these vectors contains redundant dimensions due to the existence of...
Spinal cord segmentation is an important step to empirically quantify spinal cord atrophy that can occur in neurological diseases such as multiple sclerosis (MS). In this work, we propose a novel method to find the globally optimal segmentation of the spinal cord using a high dimensional minimal path search. The spinal cord cross-sectional shapes are represented using principal component analysis...
Many desirable applications dealing with automatic face analysis rely on robust facial feature localization. While extensive research has been carried out on standard 2D imagery, recent technological advances made the acquisition of 3D data both accurate and affordable, opening new ways to more accurate and robust algorithms. We present a model-based approach to real time face alignment, fitting a...
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