From 3D Point Clouds to Pose-Normalised Depth Maps

We consider the problem of generating either pairwise-aligned or pose-normalised depth maps from noisy 3D point clouds in a relatively unrestricted poses. Our system is deployed in a 3D face alignment application and consists of the following four stages: (i) data filtering, (ii) nose tip identification and sub-vertex localisation, (iii) computation of the (relative) face orientation, (iv) generation of either a pose aligned or a pose normalised depth map. We generate an implicit radial basis function (RBF) model of the facial surface and this is employed within all four stages of the process. For example, in stage (ii), construction of novel invariant features is based on sampling this RBF over a set of concentric spheres to give a spherically-sampled RBF (SSR) shape histogram. In stage (iii), a second novel descriptor, called an isoradius contour curvature signal, is defined, which allows rotational alignment to be determined using a simple process of 1D correlation. We test our system on both the University of York (UoY) 3D face dataset and the Face Recognition Grand Challenge (FRGC) 3D data. For the more challenging UoY data, our SSR descriptors significantly outperform three variants of spin images, successfully identifying nose vertices at a rate of 99.6%. Nose localisation performance on the higher quality FRGC data, which has only small pose variations, is 99.9%. Our best system successfully normalises the pose of 3D faces at rates of 99.1% (UoY data) and 99.6% (FRGC data)

Analysis of the inspection of mechanical parts using dense range data

More than ever, efficiency and quality are key words in modern industry. This situation enhances the importance of quality control and creates a great demand for cheap and reliable automatic inspection systems. Taking into account these facts and the demand for systems able to inspect the final shape of machined parts, we decided to investigate the viability of automatic model-based inspection of mechanical parts using the dense range data produced by laser stripers. Given a part to be inspected and a corresponding model of the part stored in the model data base, the first step of inspecting the part is the acquisition of data corresponding to the part, in our case this means the acquisition of a range image of it. In order to be able to compare the part image and its stored model, it is necessary to align the model with the range image of the part. This process, called registration, corresponds to finding the rigid transformation that superposes model and image. After the image and model are registered, the actual inspection uses the range image to verify if all the features predicted in the model are present and have the right pose and dimensions. Therefore, besides the acquisition of range images, the inspection of machined parts involves three main issues: modelling, registration and inspection diagnosis. The application, for inspection purposes, of the main representational schemes for modelling solid objects is discussed and it is suggested the use of EDT models (see [Zeid 91]). A particular implementation of EDT models is presented. A novel approach for the verification of tolerances during the inspection is proposed. The approach allows not only the inspection of the most common tolerances described in the tolerancing standards, but also the inspection of tolerances defined according to Requicha's theory of tolerancing (see [Requicha 83]). A model of the sensitivity and reliability of the inspection process based on the modelling of the errors during the inspection process is also proposed. The importance of the accuracy of the registration in different inspections tasks is discussed. A modified version of the ICP algorithm (see [Besl &; McKay 92]) for the registration of sculptured surfaces is proposed. The maximum accuracy of the ICP algorithm, as a function of the sensor errors and the number of matched points, is determined. A novel method for the measurement and reconstruction of waviness errors on sculp¬ tured surfaces is proposed. The method makes use of the 2D Discrete Fourier Transform for the detection and reconstruction of the waviness error. A model of the sensitivity and reliability of the method is proposed. The application of the methods proposed is illustrated using synthetic and real range image

3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks

We propose a method for reconstructing 3D shapes from 2D sketches in the form of line drawings. Our method takes as input a single sketch, or multiple sketches, and outputs a dense point cloud representing a 3D reconstruction of the input sketch(es). The point cloud is then converted into a polygon mesh. At the heart of our method lies a deep, encoder-decoder network. The encoder converts the sketch into a compact representation encoding shape information. The decoder converts this representation into depth and normal maps capturing the underlying surface from several output viewpoints. The multi-view maps are then consolidated into a 3D point cloud by solving an optimization problem that fuses depth and normals across all viewpoints. Based on our experiments, compared to other methods, such as volumetric networks, our architecture offers several advantages, including more faithful reconstruction, higher output surface resolution, better preservation of topology and shape structure.Comment: 3DV 2017 (oral

A view-based deformation tool-kit, Master\u27s Thesis, August 2006

Camera manipulation is a hard problem since a graphics camera is defined by specifying 11 independent parameters. Manipulating such a high-dimensional space to accomplish specific tasks is difficult and requires a certain amount of expertise. We present an intuitive interface that allows novice users to perform camera operations in terms of the change they want see in the image. In addition to developing a natural means for camera interaction, our system also includes a novel interface for viewing and organizing previously saved views. When exploring complex 3D data-sets a single view is not sufficient. Instead, a composite view built from multiple views may be more useful. While changing a single camera is hard enough, manipulating several cameras in a single scene is still harder. In this thesis, we also present a framework for creating composite views and an interface that allows users to manipulate such views in real-time

Dissecting the active galactic nucleus in Circinus -- I. Peculiar mid-IR morphology explained by a dusty hollow cone

Recent high angular resolution observations resolved for the first time the mid-infrared (MIR) structure of nearby active galactic nuclei (AGN). Surprisingly, they revealed that a major fraction of their MIR emission comes from the polar regions. This is at odds with the expectation based on AGN unification, which postulates a dusty torus in the equatorial region. The nearby, archetypical AGN in the Circinus galaxy offers one of the best opportunities to study the MIR emission in greater detail. New, high quality MIR images obtained with the upgraded VISIR instrument at the Very Large Telescope show that the previously detected bar-like structure extends up to at least 40 pc on both sides of the nucleus along the edges of the ionization cone. Motivated by observations across a wide wavelength range and on different spatial scales, we propose a phenomenological dust emission model for the AGN in the Circinus galaxy consisting of a compact dusty disk and a large-scale dusty cone shell, illuminated by a tilted accretion disk with an anisotropic emission pattern. Undertaking detailed radiative transfer simulations, we demonstrate that such a model is able to explain the peculiar MIR morphology and account for the entire IR spectral energy distribution. Our results call for caution when attributing dust emission of unresolved sources entirely to the torus and warrant further investigation of the MIR emission in the polar regions of AGN.Comment: Accepted to MNRAS. Version 2: typos correcte

Detecting the orientation of magnetic fields in galaxy clusters

Clusters of galaxies, filled with hot magnetized plasma, are the largest bound objects in existence and an important touchstone in understanding the formation of structures in our Universe. In such clusters, thermal conduction follows field lines, so magnetic fields strongly shape the cluster's thermal history; that some have not since cooled and collapsed is a mystery. In a seemingly unrelated puzzle, recent observations of Virgo cluster spiral galaxies imply ridges of strong, coherent magnetic fields offset from their centre. Here we demonstrate, using three-dimensional magnetohydrodynamical simulations, that such ridges are easily explained by galaxies sweeping up field lines as they orbit inside the cluster. This magnetic drape is then lit up with cosmic rays from the galaxies' stars, generating coherent polarized emission at the galaxies' leading edges. This immediately presents a technique for probing local orientations and characteristic length scales of cluster magnetic fields. The first application of this technique, mapping the field of the Virgo cluster, gives a startling result: outside a central region, the magnetic field is preferentially oriented radially as predicted by the magnetothermal instability. Our results strongly suggest a mechanism for maintaining some clusters in a 'non-cooling-core' state.Comment: 48 pages, 21 figures, revised version to match published article in Nature Physics, high-resolution version available at http://www.cita.utoronto.ca/~pfrommer/Publications/pfrommer-dursi.pd