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This paper proposes a new method for comparing 3D facial shapes using facial level curves. The pair- and segment-wise distances between the level curves comprise the spatio-temporal features for expression recognition from 3D dynamic faces. The paper further introduces universal background modeling and maximum a posteriori adaptation for hidden Markov models, leading to a decision boundary focus classification...
Recent years have seen increased use of Computed Tomography (CT) based Unaccompanied Baggage and Package Screening (UBPS) systems for luggage examination to ensure air travel security. In this paper we present a research work on developing a system for automatic detection of potential threat items in cluttered 3D CT imagery originating from UBPS systems by combining 3D medical image segmentation techniques...
Dyslexia severely impairs learning abilities, so that improved diagnostic methods are called for. Neuropathological studies have revealed abnormal anatomy of the Corpus Callosum (CC) in dyslexic brains. We explore a possibility of distinguishing between dyslexic and normal (control) brains by quantitative CC shape analysis in 3D magnetic resonance images (MRI). Our approach consists of the three steps:...
A novel approach for shape modeling of the corpus callosum (cc) is introduced where the contours of the cc are extracted by image/volume segmentation, and a Bezier curve is used to connect the vertices of the sampled contours, generating a parametric polynomial representation. These polynomials are shown to maintain the characteristics of the original cc, thus are suitable for classification of populations...
Left ventricular (LV) remodeling is usually assessed using changes in LV volume, while disregarding regional changes that may occur independently of volume. We hypothesized that 3D analysis of regional endocardial curvature could provide useful information on localized remodeling. Cardiac magnetic resonance (CMR) images were acquired in 44 patients: 14 normal controls (NL), 15 with dilated cardiomyopathy...
This paper describes an image segmentation and normalization technique using 3D point distribution model and its counterpart in 2D space. This segmentation is efficient to work for holistic image recognition algorithm. The results have been tested with face recognition application using Cohn Kanade facial expressions database (CKFED). The approach follows by fitting a model to face image and registering...
In this paper, we propose a novel predictive model for object boundary, which can integrate information from any sources. The model is a dynamic ldquoobjectrdquo model whose manifestation includes a deformable surface representing shape, a volumetric interior carrying appearance statistics, and an embedded classifier that separates object from background based on current feature information. Unlike...
This paper presents a method for accurately segmenting and classifying 3D range data into particular object classes. Object classification of input images is necessary for applications including robot navigation and automation, in particular with respect to path planning. To achieve robust object classification, we propose the idea of an object feature which represents a distribution of neighboring...
We present work on vision based robotic grasping. The proposed method relies on extracting and representing the global contour of an object in a monocular image. A suitable grasp is then generated using a learning framework where prototypical grasping points are learned from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for...
Accurate and automatic colonic polyp segmentation and measurement in Computed Tomography (CT) has significant importance for 3D polyp detection, classification, and more generally computer aided diagnosis of colon cancers. In this paper, we propose a three-staged probabilistic binary classification approach for automatically segmenting polyp voxels from their surrounding tissues in CT. Our system...
Subcellular organelles are commonly analyzed using 2D fluorescent microscopy. However, 3D reconstruction and analysis of organelle topology in a high-throughput manner promises to result in a better understanding of cellular systems. We developed image analysis methods for automated quantitative analysis of peroxisome shapes. The methods employ 3D image stacks obtained by confocal microscopy. There...
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