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The problem of simultaneously estimating affine deformations between multiple objects occur in many applications. Herein, a direct method is proposed which provides the result as a solution of a linear system of equations without establishing correspondences between the objects. The key idea is to construct enough linearly independent equations using covariant functions, and then finding the solution...
To characterize the brain changes associated with aging, we detect brain cortex variability through a spherical harmonic analysis that represents a 3D surface supported by the unit sphere through a linear combination of special basis functions, called spherical harmonics (SHs). The proposed 3D shape analysis is carried out in four steps: (i) 3D Delau-nay triangulation to construct a 3D mesh model...
An automated histology analysis is proposed for classification of local image patches of colon histopathology images into four principle classes: normal, cancer, adenomatous and inflamed classes. Shape features based on stroma, lumen and imperfectly segmented nuclei are combined with texture features for classification. The classification is analyzed under the three scenarios: normal vs. abnormal,...
This paper presents a feature-driven, hierarchical shape registration algorithm. The central idea is to generate correspondences in multiple levels in a coarse-to-fine manner, with additional features incrementally inserted in each level. The registration starts from the coarsest resolution. Registration results obtained in one level serve as references for the registration in the next level. We adopt...
Inter patient shape, size and intensity variations of the prostate in transrectal ultrasound (TRUS) images challenge automatic segmentation of the prostate. In this paper we propose a variational model driven by Mumford-Shah (MS) functional for segmenting the prostate. Parametric representation of the implicit curve is derived from principal component analysis (PCA) of the signed distance representation...
Variations in inter-patient prostate shape, and size and imaging artifacts in magnetic resonance images (MRI) hinders automatic accurate prostate segmentation. In this paper we propose a graph cut based energy minimization of the posterior probabilities obtained in a supervised learning schema for automatic 3D segmentation of the prostate in MRI. A probabilistic classification of the prostate voxels...
This paper tackles the matching problem of partial deformable shapes with changing boundary and varying topology. We compute high-order graph matching directly on manifolds, without global/local surface parameterization. In particular, we articulate the heat kernel tensor (HKT), which is a high-order potential of geometric compatibility between feature tuples measured by heat kernels within bounded...
We present a novel motion descriptor for gesture recognition based on depth camera. Since each object motion leads to a specific depth change characterized by depth difference, we can recognize object motion via Depth Difference Distribution (DDD) in object region. The DDD is approximated by DDD descriptor in three steps. First, each pixel's depth difference value is quantified into Depth Difference...
Optical consistency between the real world and the virtual objects is one of the important issues in Augmented Reality (AR). This paper proposes a method to estimate illuminations from an object shadow and incomplete object shape information captured by an RGB-D camera. The environmental illumination can be estimated without any prior knowledge of the object shape. The radiance of each light source...
Despite their high stability and compactness, affine moment invariants have received a relatively little attention in action recognition literature. In this paper, we introduce an approach for activity recognition, based on affine moment invariants. In the proposed approach, a compact computationally-efficient shape descriptor is developed by using affine moment invariants. Affine moment invariants...
Comparing with conventional character normalization methods not taking the discriminative information into account, this paper proposes a novel normalization method — Discriminative Normalization. Saliency regions contain most of discriminative information among similar characters. According to different types, they are enlarged in character normalization to increase their influence in recognition...
In this paper we describe the object location module of a complete floor plan understanding system. The approach relies on a Region Adjacency Graph (RAG) whose nodes correspond to connected components of the background. Two types of node attributes are proposed and are used to locate and recognize objects similar to the models or to generalize the recognition to different shapes. The tests are made...
Automatic sketch recognition is used to enhance human-computer interaction by allowing a natural/free form of interaction. It is a challenging problem due to the variability in hand drawings, the variation in the order of strokes, and the similarity of symbol classes. Since sketch recognition requires real time processing, the speed of the classifier is important. Another important issue is how to...
We present an approach to detecting near-duplicate document images using SIFT interest point matching. Given a set of document images, a database is constructed from the SIFT features extracted from each image, stored as a kd-tree. The near-duplicates of a query image are estimated by directly matching its SIFT descriptors with the feature database. We demonstrate the approach on a challenging set...
The use of high-dimension features is unavoidable in many applications of image retrieval and techniques of dimension reductions are not always efficient. The space-filling curve reduces the number of dimensions to one while preserving the neighborhood relation. In this paper, Hilbert curve, the most neighborhood preserving space-filling curve, is used in shape retrieval. The retrieving is accelerated...
Due to the high degree of freedom found in hand motion, it is difficult to model articulated hand configurations. In addition, observed hand shapes vary according to the hand rotation, even when using the same hand configuration. This paper presents a new manifold embedding method for modeling low dimensional hand configurations and hand rotation using a 4D torus manifold, in which the product of...
We propose a method for estimating 3-D hand postures from 2-D monocular images in real-time. The estimation is based on finding the best matched posture from typical postures whose appearances are learned in advance. For high accuracy, conventional methods require high computational cost for comparing an input with many typical postures. In our method, a tree is automatically generated and trained...
This paper proposes a novel method to reconstruct dynamic scenes by integrating depth data obtained by multiple Kinects, which cannot be synchronized to one another. In this method, the multiple Kinects located so as to cover the whole surface are firstly calibrated so that their depth data are mapped into the world coordinate system. The synchronous depth data for each Kinect is then generated by...
Connected operators are filtering tools that act by merging elementary regions of an image. A popular strategy is based on tree-based image representations: for example, one can compute an attribute on each node of the tree and keep only the nodes for which the attribute is sufficiently strong. This operation can be seen as a thresholding of the tree, seen as a graph whose nodes are weighted by the...
Efficiency of facial feature detection is very crucial in face related applications such as face recognition and reconstruction. Traditional algorithms of high precision are often with expensive computation. In this paper, we propose a fast facial feature detection algorithm with good precision. The basic idea is to combine fast search strategy in the global image and high precision classifier in...
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