IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 1 • Jan. 2018

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options for this item are unavailable. Select items are only available as part of a subscription package. You may try again later or contact us for more information.

Filter Results

Displaying Results 1 - 25 of 25
  • Table of Contents

    Publication Year: 2018, Page(s): C1
    Request permission for commercial reuse | |PDF file iconPDF (269 KB)
    Freely Available from IEEE
  • Cover

    Publication Year: 2018, Page(s): C2
    Request permission for commercial reuse | |PDF file iconPDF (298 KB)
    Freely Available from IEEE
  • State of the Journal

    Publication Year: 2018, Page(s):1 - 6
    Request permission for commercial reuse | |PDF file iconPDF (513 KB) | HTML iconHTML
    Freely Available from IEEE
  • Active Self-Paced Learning for Cost-Effective and Progressive Face Identification

    Publication Year: 2018, Page(s):7 - 19
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (803 KB) | HTML iconHTML Multimedia Media

    This paper aims to develop a novel cost-effective framework for face identification, which progressively maintains a batch of classifiers with the increasing face images of different individuals. By naturally combining two recently rising techniques: active learning (AL) and self-paced learning (SPL), our framework is capable of automatically annotating new instances and incorporating them into tr... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Saliency-Aware Video Object Segmentation

    Publication Year: 2018, Page(s):20 - 33
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1326 KB) | HTML iconHTML

    Video saliency, aiming for estimation of a single dominant object in a sequence, offers strong object-level cues for unsupervised video object segmentation. In this paper, we present a geodesic distance based technique that provides reliable and temporally consistent saliency measurement of superpixels as a prior for pixel-wise labeling. Using undirected intra-frame and inter-frame graphs construc... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • CODE: Coherence Based Decision Boundaries for Feature Correspondence

    Publication Year: 2018, Page(s):34 - 47
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1886 KB) | HTML iconHTML Multimedia Media

    A key challenge in feature correspondence is the difficulty in differentiating true and false matches at a local descriptor level. This forces adoption of strict similarity thresholds that discard many true matches. However, if analyzed at a global level, false matches are usually randomly scattered while true matches tend to be coherent (clustered around a few dominant motions), thus creating a c... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods

    Publication Year: 2018, Page(s):48 - 62
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (695 KB) | HTML iconHTML

    Representing images and videos with Symmetric Positive Definite (SPD) matrices, and considering the Riemannian geometry of the resulting space, has been shown to yield high discriminative power in many visual recognition tasks. Unfortunately, computation on the Riemannian manifold of SPD matrices -especially of high-dimensional ones- comes at a high cost that limits the applicability of existing t... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Direct Least Square Fitting of Hyperellipsoids

    Publication Year: 2018, Page(s):63 - 76
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1055 KB) | HTML iconHTML

    This paper presents two new computationally efficient direct methods for fitting n-dimensional ellipsoids to noisy data. They conduct the fitting by minimizing the algebraic distance in subject to suitable quadratic constraints. The hyperellipsoid-specific (HES) method is an elaboration of existing ellipse and 3D ellipsoid-specific fitting methods. It is shown that HES is ellipsoid-specific in n-d... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Discriminative Dimensionality Reduction for Multi-Dimensional Sequences

    Publication Year: 2018, Page(s):77 - 91
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1450 KB) | HTML iconHTML Multimedia Media

    Since the observables at particular time instants in a temporal sequence exhibit dependencies, they are not independent samples. Thus, it is not plausible to apply i.i.d. assumption-based dimensionality reduction methods to sequence data. This paper presents a novel supervised dimensionality reduction approach for sequence data, called Linear Sequence Discriminant Analysis (LSDA). It learns a line... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis

    Publication Year: 2018, Page(s):92 - 105
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1099 KB) | HTML iconHTML Multimedia Media

    Classical discriminant analysis attempts to discover a low-dimensional subspace where class label information is maximally preserved under projection. Canonical methods for estimating the subspace optimize an information-theoretic criterion that measures the separation between the class-conditional distributions. Unfortunately, direct optimization of the information-theoretic criteria is generally... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Generative Local Metric Learning for Nearest Neighbor Classification

    Publication Year: 2018, Page(s):106 - 118
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1045 KB) | HTML iconHTML

    We consider the problem of learning a local metric in order to enhance the performance of nearest neighbor classification. Conventional metric learning methods attempt to separate data distributions in a purely discriminative manner; here we show how to take advantage of information from parametric generative models. We focus on the bias in the information-theoretic error arising from finite sampl... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Latent-Class Hough Forests for 6 DoF Object Pose Estimation

    Publication Year: 2018, Page(s):119 - 132
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1587 KB) | HTML iconHTML

    In this paper we present Latent-Class Hough Forests, a method for object detection and 6 DoF pose estimation in heavily cluttered and occluded scenarios. We adapt a state of the art template matching feature into a scale-invariant patch descriptor and integrate it into a regression forest using a novel template-based split function. We train with positive samples only and we treat class distributi... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Light Field Reconstruction Using Shearlet Transform

    Publication Year: 2018, Page(s):133 - 147
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (2060 KB) | HTML iconHTML Multimedia Media

    In this article we develop an image based rendering technique based on light field reconstruction from a limited set of perspective views acquired by cameras. Our approach utilizes sparse representation of epipolar-plane images (EPI) in shearlet transform domain. The shearlet transform has been specifically modified to handle the straight lines characteristic for EPI. The devised iterative regular... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Longitudinal Study of Automatic Face Recognition

    Publication Year: 2018, Page(s):148 - 162
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1559 KB) | HTML iconHTML

    The two underlying premises of automatic face recognition are uniqueness and permanence. This paper investigates the permanence property by addressing the following: Does face recognition ability of state-of-the-art systems degrade with elapsed time between enrolled and query face images? If so, what is the rate of decline w.r.t. the elapsed time? While previous studies have reported degradations ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multi-Dimensional Sparse Models

    Publication Year: 2018, Page(s):163 - 178
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1933 KB) | HTML iconHTML Multimedia Media

    Traditional synthesis/analysis sparse representation models signals in a one dimensional (1D) way, in which a multidimensional (MD) signal is converted into a 1D vector. 1D modeling cannot sufficiently handle MD signals of high dimensionality in limited computational resources and memory usage, as breaking the data structure and inherently ignores the diversity of MD signals (tensors). We utilize ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multiresolution Search of the Rigid Motion Space for Intensity-Based Registration

    Publication Year: 2018, Page(s):179 - 191
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1311 KB) | HTML iconHTML Multimedia Media

    We study the relation between the correlation-based target functions of low-resolution and high-resolution intensity-based registration for the class of rigid transformations. Our results show that low-resolution target values can tightly bound the high-resolution target function in natural images. This can help with analyzing and better understanding the process of multiresolution image registrat... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Robust Guided Image Filtering Using Nonconvex Potentials

    Publication Year: 2018, Page(s):192 - 207
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (2130 KB) | HTML iconHTML

    Filtering images using a guidance signal, a process called guided or joint image filtering, has been used in various tasks in computer vision and computational photography, particularly for noise reduction and joint upsampling. This uses an additional guidance signal as a structure prior, and transfers the structure of the guidance signal to an input image, restoring noisy or altered image structu... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Robust Matrix Factorization by Majorization Minimization

    Publication Year: 2018, Page(s):208 - 220
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (3477 KB) | HTML iconHTML Multimedia Media

    $L_1$ -norm based low rank matrix factorization in the presence of missing data and outliers remains a hot topic in computer vision. Due to non-convexity and non-smoothness, all the existing methods either lack scalability or robustness, or have no ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • SymPS: BRDF Symmetry Guided Photometric Stereo for Shape and Light Source Estimation

    Publication Year: 2018, Page(s):221 - 234
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (2848 KB) | HTML iconHTML Multimedia Media

    We propose uncalibrated photometric stereo methods that address the problem due to unknown isotropic reflectance. At the core of our methods is the notion of “constrained half-vector symmetry” for general isotropic BRDFs. We show that such symmetry can be observed in various real-world materials, and it leads to new techniques for shape and light source estimation. Based on the 1D an... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The Manhattan Frame Model—Manhattan World Inference in the Space of Surface Normals

    Publication Year: 2018, Page(s):235 - 249
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1390 KB) | HTML iconHTML

    Objects and structures within man-made environments typically exhibit a high degree of organization in the form of orthogonal and parallel planes. Traditional approaches utilize these regularities via the restrictive, and rather local, Manhattan World (MW) assumption which posits that every plane is perpendicular to one of the axes of a single coordinate system. The aforementioned regularities are... View full abstract»

    Open Access
  • 2017 Reviewers List

    Publication Year: 2018, Page(s):250 - 255
    Request permission for commercial reuse | |PDF file iconPDF (57 KB)
    Freely Available from IEEE
  • Introducing IEEE Collabratec

    Publication Year: 2018, Page(s): 256
    Request permission for commercial reuse | |PDF file iconPDF (1866 KB)
    Freely Available from IEEE
  • 2017 Index IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 39

    Publication Year: 2018, Page(s):1 - 23
    Request permission for commercial reuse | |PDF file iconPDF (299 KB)
    Freely Available from IEEE
  • Cover

    Publication Year: 2018, Page(s): C3
    Request permission for commercial reuse | |PDF file iconPDF (298 KB)
    Freely Available from IEEE
  • Table of Contents [Back Cover]

    Publication Year: 2018, Page(s): C4
    Request permission for commercial reuse | |PDF file iconPDF (271 KB)
    Freely Available from IEEE

Aims & Scope

The IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is published monthly. Its editorial board strives to present most important research results in areas within TPAMI's scope.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Sven Dickinson
University of Toronto
e-mail: sven@cs.toronto.edu