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In this paper, we propose a novel method for detecting and tracking landmark facial features on purely geometric 3D and 4D range models. Our proposed method involves fitting a new multi-frame constrained 3D temporal deformable shape model (TDSM) to range data sequences. We consider this a temporal based deformable model as we concatenate consecutive deformable shape models into a single model driven...
We present a novel method to produce realistic expressions and animations by transferring existing expressions from a given facial model to a new facial model. The representation of the target model is first converted to make its topology the same as the source model. The radial basis function is employed to deform the template meshes to fit the target model. We then map all the vertices to the surface...
This paper addresses a major challenge in data-driven haptic modeling of deformable objects. Data-driven modeling is done for specific objects and is difficult to generalize for nearly isometric objects that have similarities in semantics or topology. This limitation prevents the wide use of the data-driven modeling techniques when compared with parametric methods such as finite element methods. The...
In this paper, we propose a novel vehicle tracking system under a surveillance camera. The proposed system tracks vehicles by using constrained multiple-kernel facilitated with Kalman filtering, and then continuously updates the position and the orientation by adopting a systematically built 3-D vehicle model in an evolutionary computing framework. The proposed system can thus successfully track vehicles...
Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between...
Facial expression is central to human experience. Its efficient and valid measurement is a challenge that automated facial image analysis seeks to address. Most publically available databases are limited to 2D static images or video of posed facial behavior. Because posed and un-posed (aka “spontaneous”) facial expressions differ along several dimensions including complexity and timing, well-annotated...
This paper addresses the problem of facial landmark localization on partially occluded faces. We proposes an explicit occlusion detection based deformable fitting model for occluded landmark localization. Most recent shape registration methods apply landmark local search and attempt to simultaneously minimize both the model error and localization error. However, if part of the shape is occluded, those...
Current CT techniques are able to produce isotropic high resolution CT images (0.5mm). Recent research has revealed that the interior of the left ventricle has complex structures and topology, which has potentially valuable information. However, this makes the matching between models much more challenging. In this paper, we propose a novel method to match two models with non-trivial topology. 3D mesh...
We present a hybrid framework for segmenting structures consisting of distinct inter-connected parts. We combine the robustness of Conditional Random Fields in appearance classification with the shape constraints of geometric models and the relative part topology constraints that multi-compartment modeling provides. We demonstrate the performance of our method in cell segmentation from fluorescent...
A novel correspondence-less approach is proposed to find a non-linear aligning transformation between a pair of deformable 3D objects. Herein, we consider a polynomial deformation model, but our framework can be easily adapted to other common deformations. The basic idea of the proposed method is to set up a system of nonlinear equations whose solution directly provides the parameters of the aligning...
We present a new interactive segmentation framework to delineate the prostate from MR images. We first explicitly address the segmentation problem based on fast globally Finsler Active Contours (FAC) by incorporating both statistical and geometric shape prior knowledge. In doing so, we are able to exploit the more global aspects of segmentation by incorporating user feedback in segmentation process...
The aims of this study were to present a method quantifying and visualizing the deformation of subject-specific lateral pterygoid muscles (LPM) during a simulated jaw-opening movement. A normal adult male subject underwent magnetic resonance (MR) scans of the head at three mandibular positions: mandibular rest (M0), medium jaw-opened (M1), and maximum jaw-opened (M2) positions. The 3D models of the...
Mobile devices are too small to operate freely using their input surfaces. To solve this problem, non-contact and natural gesture interfaces have been the focus of recent research. In this paper we propose a method of estimating multi-finger position and pose for operating such devices at high speed using a single camera. Our method achieves the finger tracking based on the appearance and shape deformation...
Recently, 3D body shape information is widely effective in various applications and markets such as apparel industry or health management. However, existing techniques to obtain 3D body shape have been highly expensive and complex, or not performed modeling despite required anatomical information. We propose a simple system for obtaining 3D body shape using only a few photos captured by users themselves...
An pipeline for reconstructing the 3D face model from an uncontrolled video sequence is presented which involves three major steps. Firstly, a generic deformable 3D face model is built from the 3D scans of one hundred individuals. Secondly, the 3D face shape from a video sequence is constructed by estimating poses of images using structure-from-motion technique and dense correspondences between those...
The quality of biometric samples plays an important role in biometric authentication systems because it has a direct impact on verification or identification performance. In this paper, we present a novel 3D face recognition system which performs quality assessment on input images prior to recognition. More specifically, a reject option is provided to allow the system operator to eliminate the incoming...
This paper presents a method of learning global and reconfigurable part-based models (RPM) for object detection. Recently, deformable part-based model (DPM) is widely used. A DPM consists of a root node and a collection of part nodes, which is learned under the latent SVM formulation by treating part nodes as hidden variables. Although the configuration of parts (i.e., the shapes, sizes and locations...
In this paper, a new snake external force is proposed as the gradient of the image local energy diffusion potential. The local energy is computed using a bank of orthogonal log Gabor filters. The proposed Local Energy Diffusion Field (LEDF) is computed by energy diffusion Partial Differential Equation (PDE). The results of the LEDF snake were compared with the GVF snake in terms of capture range,...
Based on spring-mass model, which can effectively represent the mechanical behavior of fabric and simulate its complex deformation, a mathematical model is established using such basic fabric mechanical data as tensile, shear and bending from KES testing system. And then the fabric and skirt static appearance is simulated vividly by computer programming for the mathematical model. The system simulating...
Pictorial Structures (PS) define a probabilistic model of 2D articulated objects in images. Typical PS models assume an object can be represented by a set of rigid parts connected with pairwise constraints that define the prior probability of part configurations. These models are widely used to represent non-rigid articulated objects such as humans and animals despite the fact that such objects have...
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