IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 8 • Aug. 2017

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Displaying Results 1 - 19 of 19
  • Table of Contents

    Publication Year: 2017, Page(s): C1
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  • Cover

    Publication Year: 2017, Page(s): C2
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  • A Tube-and-Droplet-Based Approach for Representing and Analyzing Motion Trajectories

    Publication Year: 2017, Page(s):1489 - 1503
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1205 KB) | HTML iconHTML

    Trajectory analysis is essential in many applications. In this paper, we address the problem of representing motion trajectories in a highly informative way, and consequently utilize it for analyzing trajectories. Our approach first leverages the complete information from given trajectories to construct a thermal transfer field which provides a context-rich way to describe the global motion patter... View full abstract»

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  • Automatic Trimap Generation and Consistent Matting for Light-Field Images

    Publication Year: 2017, Page(s):1504 - 1517
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1849 KB) | HTML iconHTML

    In this paper, we introduce an automatic approach to generate trimaps and consistent alpha mattes of foreground objects in a light-field image. Our method first performs binary segmentation to roughly segment a light-field image into foreground and background based on depth and color. Next, we estimate accurate trimaps through analyzing color distribution along the boundary of the segmentation usi... View full abstract»

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  • Blind Image Denoising via Dependent Dirichlet Process Tree

    Publication Year: 2017, Page(s):1518 - 1531
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1262 KB) | HTML iconHTML

    Most existing image denoising approaches assumed the noise to be homogeneous white Gaussian distributed with known intensity. However, in real noisy images, the noise models are usually unknown beforehand and can be much more complex. This paper addresses this problem and proposes a novel blind image denoising algorithm to recover the clean image from noisy one with the unknown noise model. To mod... View full abstract»

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  • Characterizing and Discovering Spatiotemporal Social Contact Patterns for Healthcare

    Publication Year: 2017, Page(s):1532 - 1546
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1905 KB) | HTML iconHTML

    During an epidemic, the spatial, temporal and demographic patterns of disease transmission are determined by multiple factors. In addition to the physiological properties of the pathogens and hosts, the social contact of the host population, which characterizes the reciprocal exposures of individuals to infection according to their demographic structure and various social activities, are also pivo... View full abstract»

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  • Clustering by Minimum Cut Hyperplanes

    Publication Year: 2017, Page(s):1547 - 1560
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1914 KB) | HTML iconHTML Multimedia Media

    Minimum normalised graph cuts are highly effective ways of partitioning unlabeled data, having been made popular by the success of spectral clustering. This work presents a novel method for learning hyperplane separators which minimise this graph cut objective, when data are embedded in Euclidean space. The optimisation problem associated with the proposed method can be formulated as a sequence of... View full abstract»

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  • Discriminative Scale Space Tracking

    Publication Year: 2017, Page(s):1561 - 1575
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (973 KB) | HTML iconHTML

    Accurate scale estimation of a target is a challenging research problem in visual object tracking. Most state-of-the-art methods employ an exhaustive scale search to estimate the target size. The exhaustive search strategy is computationally expensive and struggles when encountered with large scale variations. This paper investigates the problem of accurate and robust scale estimation in a trackin... View full abstract»

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  • Novel Views of Objects from a Single Image

    Publication Year: 2017, Page(s):1576 - 1590
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1973 KB) | HTML iconHTML

    Taking an image of an object is at its core a lossy process. The rich information about the three-dimensional structure of the world is flattened to an image plane and decisions such as viewpoint and camera parameters are final and not easily revertible. As a consequence, possibilities of changing viewpoint are limited. Given a single image depicting an object, novel-view synthesis is the task of ... View full abstract»

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  • Robust Multiview Photometric Stereo Using Planar Mesh Parameterization

    Publication Year: 2017, Page(s):1591 - 1604
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (2777 KB) | HTML iconHTML Multimedia Media

    We propose a robust uncalibrated multiview photometric stereo method for high quality 3D shape reconstruction. In our method, a coarse initial 3D mesh obtained using a multiview stereo method is projected onto a 2D planar domain using a planar mesh parameterization technique. We describe methods for surface normal estimation that work in the parameterized 2D space that jointly incorporates all geo... View full abstract»

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  • Saliency Detection on Light Field

    Publication Year: 2017, Page(s):1605 - 1616
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1781 KB) | HTML iconHTML

    Existing saliency detection approaches use images as inputs and are sensitive to foreground/background similarities, complex background textures, and occlusions. We explore the problem of using light fields as input for saliency detection. Our technique is enabled by the availability of commercial plenoptic cameras that capture the light field of a scene in a single shot. We show that the unique r... View full abstract»

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  • Semantic Pooling for Complex Event Analysis in Untrimmed Videos

    Publication Year: 2017, Page(s):1617 - 1632
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (683 KB) | HTML iconHTML Multimedia Media

    Pooling plays an important role in generating a discriminative video representation. In this paper, we propose a new semantic pooling approach for challenging event analysis tasks (e.g., event detection, recognition, and recounting) in long untrimmed Internet videos, especially when only a few shots/segments are relevant to the event of interest while many other shots are irrelevant or even mislea... View full abstract»

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  • Social Collaborative Filtering by Trust

    Publication Year: 2017, Page(s):1633 - 1647
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (717 KB) | HTML iconHTML

    Recommender systems are used to accurately and actively provide users with potentially interesting information or services. Collaborative filtering is a widely adopted approach to recommendation, but sparse data and cold-start users are often barriers to providing high quality recommendations. To address such issues, we propose a novel method that works to improve the performance of collaborative ... View full abstract»

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  • Sparse Representation for 3D Shape Estimation: A Convex Relaxation Approach

    Publication Year: 2017, Page(s):1648 - 1661
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1155 KB) | HTML iconHTML Multimedia Media

    We investigate the problem of estimating the 3D shape of an object defined by a set of 3D landmarks, given their 2D correspondences in a single image. A successful approach to alleviating the reconstruction ambiguity is the 3D deformable shape model and a sparse representation is often used to capture complex shape variability. But the model inference is still challenging due to the nonconvexity i... View full abstract»

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  • Tri-Clustered Tensor Completion for Social-Aware Image Tag Refinement

    Publication Year: 2017, Page(s):1662 - 1674
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (2889 KB) | HTML iconHTML

    Social image tag refinement, which aims to improve tag quality by automatically completing the missing tags and rectifying the noise-corrupted ones, is an essential component for social image search. Conventional approaches mainly focus on exploring the visual and tag information, without considering the user information, which often reveals important hints on the (in)correct tags of social images... View full abstract»

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  • Uniform Projection for Multi-View Learning

    Publication Year: 2017, Page(s):1675 - 1689
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (729 KB) | HTML iconHTML

    Multi-view learning aims to integrate multiple data information from different views to improve the learning performance. The key problem is to handle the unconformities or distortions among view-specific samples or measurements of similarity or dissimilarity. This paper models the view-specific samples as a nonlinear mapping of uniform but latent intact samples for all the views, and the view-spe... View full abstract»

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  • Sparse Representation-Based Open Set Recognition

    Publication Year: 2017, Page(s):1690 - 1696
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (597 KB)

    We propose a generalized Sparse Representation-based Classification (SRC) algorithm for open set recognition where not all classes presented during testing are known during training. The SRC algorithm uses class reconstruction errors for classification. As most of the discriminative information for open set recognition is hidden in the tail part of the matched and sum of non-matched reconstruction... View full abstract»

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  • Cover

    Publication Year: 2017, Page(s): C3
    Request permission for commercial reuse | |PDF file iconPDF (297 KB)
    Freely Available from IEEE
  • Cover

    Publication Year: 2017, Page(s): C4
    Request permission for commercial reuse | |PDF file iconPDF (275 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