160 research outputs found

    Ensemble of Different Approaches for a Reliable Person Re-identification System

    Get PDF
    An ensemble of approaches for reliable person re-identification is proposed in this paper. The proposed ensemble is built combining widely used person re-identification systems using different color spaces and some variants of state-of-the-art approaches that are proposed in this paper. Different descriptors are tested, and both texture and color features are extracted from the images; then the different descriptors are compared using different distance measures (e.g., the Euclidean distance, angle, and the Jeffrey distance). To improve performance, a method based on skeleton detection, extracted from the depth map, is also applied when the depth map is available. The proposed ensemble is validated on three widely used datasets (CAVIAR4REID, IAS, and VIPeR), keeping the same parameter set of each approach constant across all tests to avoid overfitting and to demonstrate that the proposed system can be considered a general-purpose person re-identification system. Our experimental results show that the proposed system offers significant improvements over baseline approaches. The source code used for the approaches tested in this paper will be available at https://www.dei.unipd.it/node/2357 and http://robotics.dei.unipd.it/reid/

    Geometric origin of mechanical properties of granular materials

    Full text link
    Some remarkable generic properties, related to isostaticity and potential energy minimization, of equilibrium configurations of assemblies of rigid, frictionless grains are studied. Isostaticity -the uniqueness of the forces, once the list of contacts is known- is established in a quite general context, and the important distinction between isostatic problems under given external loads and isostatic (rigid) structures is presented. Complete rigidity is only guaranteed, on stability grounds, in the case of spherical cohesionless grains. Otherwise, the network of contacts might deform elastically in response to load increments, even though grains are rigid. This sets an uuper bound on the contact coordination number. The approximation of small displacements (ASD) allows to draw analogies with other model systems studied in statistical mechanics, such as minimum paths on a lattice. It also entails the uniqueness of the equilibrium state (the list of contacts itself is geometrically determined) for cohesionless grains, and thus the absence of plastic dissipation. Plasticity and hysteresis are due to the lack of such uniqueness and may stem, apart from intergranular friction, from small, but finite, rearrangements, in which the system jumps between two distinct potential energy minima, or from bounded tensile contact forces. The response to load increments is discussed. On the basis of past numerical studies, we argue that, if the ASD is valid, the macroscopic displacement field is the solution to an elliptic boundary value problem (akin to the Stokes problem).Comment: RevTex, 40 pages, 26 figures. Close to published paper. Misprints and minor errors correcte

    Image Feature Information Extraction for Interest Point Detection: A Comprehensive Review

    Full text link
    Interest point detection is one of the most fundamental and critical problems in computer vision and image processing. In this paper, we carry out a comprehensive review on image feature information (IFI) extraction techniques for interest point detection. To systematically introduce how the existing interest point detection methods extract IFI from an input image, we propose a taxonomy of the IFI extraction techniques for interest point detection. According to this taxonomy, we discuss different types of IFI extraction techniques for interest point detection. Furthermore, we identify the main unresolved issues related to the existing IFI extraction techniques for interest point detection and any interest point detection methods that have not been discussed before. The existing popular datasets and evaluation standards are provided and the performances for eighteen state-of-the-art approaches are evaluated and discussed. Moreover, future research directions on IFI extraction techniques for interest point detection are elaborated

    Similarity Detection for Free-Form Parametric Models

    Get PDF
    International audienceIn this article, we propose a framework for detecting local similarities in free-form parametric models, in particular on B-Splines or NURBS based B-reps: patches similar up to an approximated isometry are identified. Many recent articles have tackled similarity detection on 3D objects, in particular on 3D meshes. The parametric B-splines, or NURBS models are standard in the CAD (Computer Aided Design) industry, and similarity detection opens the door to interesting applications in this domain, such as model editing, objects comparison or efficient coding. Our contributions are twofold: we adapt the current technique called votes transformation space for parametric surfaces and we improve the identification of isometries. First, an orientation technique independent of the parameterization permits to identify direct versus indirect transformations. Second, the validation step is generalized to extend to the whole B-rep. Then, by classifying the isometries according to their fixed points, we simplify the clustering step. We also apply an unsupervised spectral clustering method which improves the results but also automatically estimates the number of clusters

    Digital Image Access & Retrieval

    Get PDF
    The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

    Structure-aware content creation : detection, retargeting and deformation

    Get PDF
    Nowadays, access to digital information has become ubiquitous, while three-dimensional visual representation is becoming indispensable to knowledge understanding and information retrieval. Three-dimensional digitization plays a natural role in bridging connections between the real and virtual world, which prompt the huge demand for massive three-dimensional digital content. But reducing the effort required for three-dimensional modeling has been a practical problem, and long standing challenge in compute graphics and related fields. In this thesis, we propose several techniques for lightening up the content creation process, which have the common theme of being structure-aware, ie maintaining global relations among the parts of shape. We are especially interested in formulating our algorithms such that they make use of symmetry structures, because of their concise yet highly abstract principles are universally applicable to most regular patterns. We introduce our work from three different aspects in this thesis. First, we characterized spaces of symmetry preserving deformations, and developed a method to explore this space in real-time, which significantly simplified the generation of symmetry preserving shape variants. Second, we empirically studied three-dimensional offset statistics, and developed a fully automatic retargeting application, which is based on verified sparsity. Finally, we made step forward in solving the approximate three-dimensional partial symmetry detection problem, using a novel co-occurrence analysis method, which could serve as the foundation to high-level applications.Jetzt hat die Zugang zu digitalen Informationen allgegenwärtig geworden. Dreidimensionale visuelle Darstellung wird immer zum Einsichtsverständnis und Informationswiedergewinnung unverzichtbar. Dreidimensionale Digitalisierung verbindet die reale und virtuelle Welt auf natürliche Weise, die prompt die große Nachfrage nach massiven dreidimensionale digitale Inhalte. Es ist immer noch ein praktisches Problem und langjährige Herausforderung in Computergrafik und verwandten Bereichen, die den Aufwand für die dreidimensionale Modellierung reduzieren. In dieser Dissertation schlagen wir verschiedene Techniken zur Aufhellung der Erstellung von Inhalten auf, im Rahmen der gemeinsamen Thema der struktur-bewusst zu sein, d.h. globalen Beziehungen zwischen den Teilen der Gestalt beibehalten wird. Besonders interessiert sind wir bei der Formulierung unserer Algorithmen, so dass sie den Einsatz von Symmetrische Strukturen machen, wegen ihrer knappen, aber sehr abstrakten Prinzipien für die meisten regelmäßigen Mustern universell einsetzbar sind. Wir stellen unsere Arbei aus drei verschiedenen Aspekte in dieser Dissertation. Erstens befinden wir Räume der Verformungen, die Symmetrien zu erhalten, und entwickelten wir eine Methode, diesen Raum in Echtzeit zu erkunden, die deutlich die Erzeugung von Gestalten vereinfacht, die Symmetrien zu bewahren. Zweitens haben wir empirisch untersucht dreidimensionale Offset Statistiken und entwickelten eine vollautomatische Applikation für Retargeting, die auf den verifizierte Seltenheit basiert. Schließlich treten wir uns auf die ungefähre dreidimensionalen Teilsymmetrie Erkennungsproblem zu lösen, auf der Grundlage unserer neuen Kookkurrenz Analyseverfahren, die viele hochrangige Anwendungen dienen verwendet werden könnten

    Statistical Modelling of Craniofacial Shape

    Get PDF
    With prior knowledge and experience, people can easily observe rich shape and texture variation for a certain type of objects, such as human faces, cats or chairs, in both 2D and 3D images. This ability helps us recognise the same person, distinguish different kinds of creatures and sketch unseen samples of the same object class. The process of capturing this prior knowledge is mathematically interpreted as statistical modelling. The outcome is a morphable model, a vector space representation of objects, that captures the variation of shape and texture. This thesis presents research aimed at constructing 3DMMs of craniofacial shape and texture using new algorithms and processing pipelines to offer enhanced modelling abilities over existing techniques. In particular, we present several fully automatic modelling approaches and apply them to a large dataset of 3D images of the human head, the Headspace dataset, thus generating the first public shape-and- texture 3D Morphable Model (3DMM) of the full human head. We call this the Liverpool-York Head Model, reflecting the data collection and statistical modelling respectively. We also explore the craniofacial symmetry and asymmetry in template morphing and statistical modelling. We propose a Symmetry-aware Coherent Point Drift (SA-CPD) algorithm, which mitigates the tangential sliding problem seen in competing morphing algorithms. Based on the symmetry-constrained correspondence output of SA-CPD, we present a symmetry-factored statistical modelling method for craniofacial shape. Also, we propose an iterative process of refinement for a 3DMM of the human ear that employs data augmentation. Then we merge the proposed 3DMMs of the ear with the full head model. As craniofacial clinicians like to look at head profiles, we propose a new pipeline to build a 2D morphable model of the craniofacial sagittal profile and augment it with profile models from frontal and top-down views. Our models and data are made publicly available online for research purposes
    • …
    corecore