Surface Reconstruction

We study the problem of computing a planar curve, restricted to lie between two given polygonal chains, such that the integral of the square of arc-length derivative of curvature along the curve is minimized. We introduce the minimum variation B-spline problem, which is a linearly constrained optimization problem over curves, defined by B-spline functions only. An empirical investigation indicates that this problem has one unique solution among all uniform quartic B-spline functions. Furthermore, we prove that, for any B-spline function, the convexity properties of the problem are preserved subject to a scaling and translation of the knot sequence defining the B-spline.

To identify adult human buccal epithelial stem cells (SCs) on the basis of two parameters (high p63 expression and greater nucleus/cytoplasmic (N/C) ratio) and to evaluate clinical efficacy of ex-vivo expanded autologous epithelium in bilateral limbal SC-deficient (LSCD) patients. The epithelial cells were isolated from buccal biopsy and cultured on human amnion in culture inserts with 3T3 feeder layer. The SCs were identified on the basis of two-parameter analysis using confocal microscopy, surface markers, and colony-forming efficiency (CFE). The cultured epithelium was transplanted in 10 LSCD patients followed by penetrating keratoplasty in 4 patients. The clinical outcome was followed up to 3 years. A distinct population (3.0±1.7%) of small cells expressing high levels of p63 with greater N/C ratio was observed in buccal epithelium. The N/C ratio was found to be more appropriate than cell diameter for two-parameter analysis. These cells located in the basal layer were negative f...

We propose a unification framework for three-dimensional shape reconstruction using physically based models. A variety of 3D shape reconstruction techniques have been developed in the past two decades, such as shape from stereopsis, from shading, from texture gradient, and from structured lighting. However, the lack of a general theory that unifies these shape reconstruction techniques into one framework hinders the effort of a synergistical image interpretation scheme using multiple sensors/information sources. Most shape-from-X techniques use an “observable” (e.g., the stereo disparity, intensity, or texture gradient) and a model, which is based on specific domain knowledge (e.g., the triangulation principle, reflectance function, or texture distortion equation) to predict the observable, in 3D shape reconstruction. We show that all these “observable–prediction-model” types of techniques can be incorporated into our framework of energy constraint on a flexible, deformable image frame. In our algorithm, if the observable does not confirm to the predictions obtained using the corresponding model, a large “error” potential results. The error potential gradient forces the flexible image frame to deform in space. The deformation brings the flexible image frame to “wrap” onto the surface of the imaged 3D object. Surface reconstruction is thus achieved through a “package wrapping” or a “shape deformation” process by minimizing the discrepancy in the observable and the model prediction. The dynamics of such a wrapping process are governed by the least action principle which is physically correct. A physically based model is essential in this general shape reconstruction framework because of its capability to recover the desired 3D shape, to provide an animation sequence of the reconstruction, and to include the regularization principle into the theory of surface reconstruction.

We present an approach to synthesize the subtle 3D re-lief and texture of oil painting brush strokes from a single photograph. This task is unique from traditional synthesize algorithms due to its mixed modality between the input and output; i.e., our goal is to synthesize surface normals given an intensity image input. To accomplish this task, we pro-pose a framework that first applies intrinsic image decom-position to produce a pair of initial normal maps. These maps are combined into a conditional random field (CR-F) optimization framework that incorporates additional in-formation derived from a training set consisting of normals captured using photometric stereo on oil paintings with sim-ilar brush styles. Additional constraints are incorporated into the CRF framework to further ensures smoothness and preserve brush stroke edges. Our results show that this ap-proach can produce compelling reliefs that are often indis-tinguishable from results captured using photometric stere-o. 1.

9
th International Conference on Signal and Image Processing (Signal 2022) is a forum for
presenting new advances and research results in the fields of Digital Image Processing. The
conference will bring together leading researchers, engineers and scientists in the domain of
interest from around the world. The scope of the conference covers all theoretical and practical
aspects of the Signal, Image Processing & Pattern Recognition.

The widely used Stillinger-Weber potential for silicon interactions has been modified to provide an accurate description of the Si(111)-(7 × 7) surface including the highly reactive adatom and rest-atom sites. This modified potential also provides a good representation of bulk silicon, and the Si(001)-(1 × 1), Si(001)-(2 × 1), Si(111)-(1 × 1) and Si(111)-(2 × 1) surfaces. Above the melting temperature of 1683 K, however, the original Stillinger-Weber potential is probably superior.

Image stabilisation (IS) is a family of approaches whose aim is to reduce motion blur in still images and shaking effect in video frames. A variety of techniques are currently implemented in cameras and camcorders: some involve hardware solutions, other are software approaches. In general, IS for still photography entails hardware in-camera or in-lens solutions. Video stabilisation, on the other hand, can be accomplished with software algorithms, either in real-time within the camera or in post-processing. Whereas IS aids photography and video making, its influence on the photogrammetric 3D modelling process has not been investigated. This article addresses this aspect. To this purpose, several laboratory and real-world tests were carried out, whose results showed that IS must be disabled when accuracy matters in photogrammetric projects. Details are provided in the manuscript.

While there has been significant progress in the treatment of ischemic heart failure, it remains a significant health and economic problem worldwide. In this paper, we present the challenges of modelling ischemic heart failure and introduce a user-friendly software system that will be a sub-set of the Virtual Pathological Heart environment which is currently being developed under the FP7 VPH2

With the advent of new, low-cost 3D sensing hardware such as the Kinect, and continued efforts in advanced point cloud processing, 3D perception gains more and more importance in robotics, as well as other fields. In this paper we present one of our most recent initiatives in the areas of point cloud perception: PCL (Point Cloud Library - http://pointclouds.org). PCL presents an advanced and extensive approach to the subject of 3D perception, and it's meant to provide support for all the common 3D building blocks that applications need. The library contains state-of-the art algorithms for: filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation. PCL is supported by an international community of robotics and perception researchers. We provide a brief walkthrough of PCL including its algorithmic capabilities and implementation strategies.