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Recovering a deformable surface's 3D shape from a single view registered to a 3D template requires one to provide additional constraints. A recent approach has been to constrain the surface to deform quasi-isometrically. This is applicable to surfaces of materials such as paper and cloth. Current ‘closed-form’ solutions solve a convex approximation of the original problem whereby the surface's depth...
Recovering 3D geometry from a single 2D line drawing is an important and challenging problem in computer vision. It has wide applications in interactive 3D modeling from images, computer-aided design, and 3D object retrieval. Previous methods of 3D reconstruction from line drawings are mainly based on a set of heuristic rules. They are not robust to sketch errors and often fail for objects that do...
A comparative analysis of three important shape analysis techniques viz. real spherical harmonic (RSH) coefficient, shape signatures based on ray-tracing, and multi-resolution attributed contour tree (MACT) is performed to understand their strengths and weaknesses in terms of their shape description power and computational ability. The analysis is performed on anti-HIV ligands extracted from NCI database...
There are not so many 3D profile tools specially designed for specifically narrow space, for example, to scan the tooth shape of a human jaw. In this paper, a real-time 3D intraoral scanner based on piezoelectric transducer is presented for the measurement of tooth profile in the mouth cavity. The proposed system comprises a laser diode beam, a micro charge-coupled device, a graticule, a piezoelectric...
This paper addresses the issue of Gender Classification from 3D facial images. While most of previous work in the literature focuses on either 2D facial images, here, we study the use of 3D facial shape for automatic gender classification. After a preprocessing step to extract the facial masks from triangular meshes obtained using laser range scanners, we approximate the facial surfaces by collections...
We develop a feature-based shape- and motion-estimation scheme for moving radar targets based on the solution of object-image relations (OIRs) for incomplete and noisy data. Unlike previous OIR-based techniques for the radar moving-target-imaging problem, our approach is robust to 1) missing data, 2) so-called “slippery scatterers” whose location moves with respect to the radar viewing aspect, and...
Femoral strength is estimated in clinical routine from 2D Dual-energy X-rays Absorptiometry (DXA). In this study, a new pipeline for femoral strength prediction from DXA images is presented, using a 3D reconstruction method of the shape and the Bone Mineral Density (BMD) distribution and a regression analysis based on partial least squares. A database of 90 proximal femoral cadaveric specimens, that...
Industrial automation tasks typically require a 3D model of the object for robotic manipulation. The ability to reconstruct the 3D model using a sample object is useful when CAD models are not available. For textureless objects, visual hull of the object obtained using silhouette-based reconstruction can avoid expensive 3D scanners for 3D modeling. We propose convex brick (CB), a new 3D primitive...
In this paper, we discuss an object recognition and tracking system that utilizes the depth information from a low-cost depth sensor. Conventional object recognition methods that utilize RGB cameras are unable to accurately identify objects in the real world since they do not take into consideration the shape and three-dimensional characteristics of the object. Another major factor determining the...
Applications such as robotics and augmented reality (AR) require 3D tracking of rigid objects. In robotic applications, the availability of accurate and robust pose estimates increases reliability, whereas in AR scenarios reliable pose estimates decrease jitter. Pure vision sensor based 3D trackers require either manual initializations of pose or off-line training stages. On the other hand, trackers...
We present a novel shape from focus method for high-speed shape reconstruction in optical microscopy. While the traditional shape from focus approach heavily depends on the presence of surface texture, and requires a considerable amount of measurement time, our method is able to perform 3D reconstruction from only two images. Our method relies on the rapid projection of a binary pattern sequence,...
Reliable object recognition is a mandatory prerequisite for service robots that operate in everyday environments. Typical approaches run a single classifier for the purpose of object recognition. However, no single algorithm proved to classify across all types of objects. We propose an approach that combines the recognition result of several methods working on different features. This reduces the...
We propose a novel compact representation for stereoscopic videos - a 2D video and its depth cues. Depth cues are derived from an interactive labeling process during 2D-to-3D video conversion, they are contour points of foreground objects and a background geometric model. By using such cues and image features of 2D video frames, depth maps of the frames can be recovered. Compared with traditional...
Over the past decades, 3D face has emerged as a solution to face recognition due to its reputed invariance to lighting conditions and pose. While proposed approaches have proven their efficiency over renowned databases as FRGC, less effort was spent on studying the robustness of algorithms to quality degradations. In this paper, we present a study of the robustness of four state of the art algorithms...
We present a nose tip detection method using a novel 3D local shape descriptor called DF (Distance based Fourier) descriptor that is rotationally invariant. The DF descriptor allows us to control the degree of descriptiveness depending on the complexity of object shape. When combined with SVM (Support Vector Machine), the DF descriptor proves powerful for nose tip detection. The detection method also...
The need for mapping small objects in such areas as museum collections may be met by using laser scanning techniques which are likely the best and the most reliable. However, the costs associated with these techniques prohibit their use apart from that such objects are too fragile for repeated handling. Therefore, the alternative is the use of passive methods like stereovision. In this paper we presents...
A cardinal prerequisite for the system design of a sensor network, is to understand the geometric environment where sensor nodes are deployed. The global topology of a large-scale sensor network is often complex and irregular, possibly containing obstacles/holes. A convex network partition, so-called segmentation, is to divide a network into convex regions, such that traditional algorithms designed...
In order to overcome the shortcomings of the shape from shading (SFS) algorithm in items of clearness and smoothness of silhouette in reconstructed objects, a modified SFS algorithm is proposed in this paper. Firstly, we determine the primary factors affecting reconstruction by analyzing the Lambertian light reflection model. Secondly, we perform image restoration and background smoothing by extracting...
Facial occlusions pose significant problems for automatic face recognition systems. In this work, we propose a novel occlusion-resistant three-dimensional (3D) facial identification system. We show that, under extreme occlusions due to hair, hands, and eyeglasses, typical 3D face recognition systems exhibit poor performance. In order to deal with occlusions, our proposed system employs occlusion-resistant...
The 3D face recognition literature has many papers that represent facial shapes as collections of curves of different kinds (level-curves, iso-level curves, radial curves, profiles, geodesic polarization, iso-depth lines, iso-stripes, etc.). In contrast with the holistic approaches, the approaches that match faces based on whole surfaces, the curve-based parametrization allows local analysis of facial...
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