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The aim of this paper is to propose tools for statistical analysis of shape families using morphological operators. Given a series of shape families (or shape categories), the approach consists in empirically computing shape statistics (i.e., mean shape and variance of shape) and then to use simple algorithms for random shape generation, for empirical shape confidence boundaries computation and for...
In this paper a method is presented for the automated identification of cephalometric anatomical landmarks in craniofacial cone-beam CT images. This method makes use of statistical models, incorporating both local appearance and shape knowledge obtained from training data. Firstly, the local appearance model captures the local intensity pattern around each anatomical landmark in the image. Secondly,...
Automatic facial expression recognition on 3D face data is still a challenging problem. In this paper we propose a novel approach to perform expression recognition automatically and flexibly by combining a Bayesian Belief Net (BBN) and Statistical facial feature models (SFAM). A novel BBN is designed for the specific problem with our proposed parameter computing method. By learning global variations...
In this paper, a novel approach for contour based 2D shape recognition is proposed, using a class of information theoretic kernels recently introduced. This kind of kernels, based on a non-extensive generalization of the classical Shannon information theory, are defined on probability measures. In the proposed approach, chain code representations are first extracted from the contours; then n-gram...
Research on complex shape recognition showed that the shape context algorithm is sensitive to relative position variation of articulation. Aimed at this problem, a shape recognition method is proposed based on local shape filling rate of various object silhouettes. We take each landmark point as a circle center and use as its radius. Then, under a particular radius, the ratio between the covered silhouette...
The objective of this research is to embed topology within the dynamic Bayesian network (DBN) formalism. This extension of a DBN (that encodes statistical or causal relationships) to a topological DBN (TDBN) allows continuous mappings (e.g., topological homeomorphisms), topological relations (e.g., homotopy equivalences) and invariance properties (e.g., surface genus, compactness) to be exploited...
In the context of the NAVIDOMASS project, the problematic of this paper concerns the clustering of historical document images. We propose a structural-based framework to handle the ancient ornamental letters data-sets. The contribution, firstly, consists of examining the structural (i.e. graph) representation of the ornamental letters, secondly, the graph matching problem is applied to the resulted...
Due to the complexity of geoscientific data, such as geochemical data, geophysical data and digital remote sensing data, traditional data mining methods, such as cluster analysis and association analysis, have limitations in resources evaluation. In this paper, a clustering algorithm is presented which has the ability to handle clusters of arbitrary shapes, sizes and densities. For association analysis,...
In this paper we propose a similarity-based clustering algorithm for handling LR-type fuzzy numbers. The proposed method does not need to specify a cluster number and initial values in which it is robust to initial values, cluster number, cluster shapes, noise and outliers for clustering LR-type fuzzy data. Numerical examples and real data demonstrate the effectiveness of the proposed clustering algorithm.
Feature matching plays an important role in many applications, including 3D reconstruction, object recognition and video understanding. Point matching has made great progress recently, while it has made little progress in the fields of line and curve matching. By computing statistics of point descriptors constructed at each edge points, this paper develops a novel method for extending point descriptors...
Grey Relational Analysis is an method of analysis and calculate the relational degree of evaluated object, which can characterize the relational degree between object with viral object. Based on the traditional Grey Relational Analysis method, an improved method of accounting Grey relational Analysis coefficient and Grey Relational Analysis degree is introduced. Through calculating relational degree...
A real-time facial expressions recognition system is developed for human-robot interaction of service robot. The proposed system is mainly composed of two subsystems: one for Active shape model(ASM) motion extraction, and one for the classification of the estimated motion. The system first uses a cascade classifier to locate the potential face regions from video frame. Then, ASM is automatically initialized...
Frequently several PhotoVoltaic (PV) plants has to be monitored by an unique supervision centre (we can say that the plants constitute a “constellation” from the point of view of storing and transferring data). In this case the analysis of the whole population of data by means of statistical approach requires long time and it is not always possible. In the paper it is presented a procedure of analysis...
Recognizing human emotions from facial expressions is highly dependent on the quality of the referred facial expression features. Conventional methods often suffer from high computation time and serious influence of environment variations. In this paper, a triangular facial feature extraction method based on a Modified Active Shape Model (MASM) is proposed. This method features considering the interactions...
Spatial scan statistic has been applied in many disease vector studies. However it rarely takes into account some relevant contextual information. As a result, the interpretation of the test results has been challenging and some interpretations could be misleading. In this study, a new technique to apply spatial scan statistic for the detection of local clusters in disease vectors is proposed. This...
The seafloor high-frequency backscatter average statistics, including the backscatter strength and the backscatter cross section, are statistically analyzed. According to Gamma distribution model of the backscatter cross section, the probability density function (PDF) of the backscatter strength is derived, and it is proved that the backscatter strength approaches a Gaussian distribution. The data...
In this paper, we propose an efficient groupwise morphometric analysis to characterize morphological variations between healthy and pathological states. The proposed framework extends the work of Baloch in which a manifold for each anatomy was constructed by collecting lossless [transformation, residual] descriptors with various transformation parameters, and the optimal set of transformation parameters...
As the power dissipated by advanced microelectronic devices continues to increase, the demand for reliability also increases. This increases the requirements on the thermal performance of every part of the system, including the heat sink. One of the objectives of this study is to examine the effect of shape of the heat sink fins on the thermal performance of the system. The pressure gradient from...
This work presents a quantitative approach for discrimination of Oral Submucous Fibrosis (OSF) to Normal Oral Mucosa (NOM) in respect to size and shape properties of the basal layer, first layer in epithelium. Practically, basal cells form the proliferative compartment of the epithelium, and therefore changes in the morphometry of basal cells may have serious implications on future cell behavior,...
Methodology for fusing multiple segmentations to produce an improved result has been useful in computational anatomical studies. Although obtaining segmentations of anatomy having a particular topology are essential to studies using diffeomorphic deformation based analyses, no methods of label fusion presented to date have incorporated information regarding the topology of the anatomy. In this paper,...
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