ÐA method for deformable shape detection and recognition is described. Deformable shape templates are used to partition the image into a globally consistent interpretation, determined in part by the minimum description length principle. Statistical shape models enforce the prior probabilities on global, parametric deformations for each object class. Once trained, the system autonomously segment...

In this paper, a new region-based active contour model, namely local region-based Chan–Vese (LRCV) model, is proposed for image segmentation. By considering the image local characteristics, the proposed model can effectively and efficiently segment images with intensity inhomogeneity. To reduce the dependency on manual initialization in many active contour models and for an automatic segmentati...

The region-based coding of the volume data is proposed in the present paper. Since the volume data is the three dimensional one, the visualization method is needed to display it. The region segmentation is indispensable to visualize the desired portions only. In the proposed method, the region segmentation result is utilized to code the volume data; the contours and the colors of the regions ar...

Image classification is a challenging problem due to intra-class appearance variation, background clutter, occlusion, and photometric variability. Current state-ofthe-art methods do not explicitly handle background clutter, but rely on global image representations, such as bag-of-word (BoW) models. Multiple-instance learning has been used to explicitly deal with clutter, classifying an image po...

Air pollution has a direct impact to human health, and data-driven air quality models are useful for evaluating population exposure to air pollutants. In this paper, we propose a novel region-based Gaussian process model for estimating urban air pollution dispersion, and applied it to a large dataset of ultrafine particle (UFP) measurements collected from a network of sensors located on several...

This paper presents a new mouth region localization method which uses the Gaussian mixture model (GMM) of feature vectors extracted from mouth region images. The discrete cosine transformation (DCT) and principle component analysis (PCA) based feature vectors are evaluated in mouth localization experiments. The new method is suitable for audio-visual speech recognition. This paper also introduc...

Iris recognition is one of the most reliable and accurate biometric technologies, as the richness and apparent stability of the iris texture make it robust. Iris segmentation is a critical part in iris recognition, because it defines the inner and outer boundaries of iris region which is used for feature analysis. Active contour model, also known as snake, is a powerful image segmentation techn...

We show a fast algorithm for region extraction based on belief propagation with loopy networks. The solution to this region segmentation problem, which includes the region extraction problem, is of significant computational cost if a conventional iterative approach or statistical sampling methods are applied. In the proposed approach, Gaussian loopy belief propagation is applied to a continuous...

A method for deformable shape detection and recognition is described. Deformable shape templates are used to partition the image into a globally consistent interpretation, determined in part by the minimum description length principle. Statistical shape models enforce the prior probabilities on global, parametric deformations for each object class. Once trained, the system autonomously segments...

the aerodynamics of road vehicles has frequently been studied in simplified geometries to separate the effect of various components on aerodynamic drag and on near wake flow dynamics. in this work, the characteristics of the near wake of a notch-back car model were investigated, using hot-wire anemometer. the main objectives of this study are to gain a better understanding of the flow structure...