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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 5 • Date May 2013

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Displaying Results 1 - 23 of 23
  • [Table of contents]

    Publication Year: 2013 , Page(s): c1
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  • Cover2

    Publication Year: 2013 , Page(s): c2
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  • A Convex Formulation for Learning a Shared Predictive Structure from Multiple Tasks

    Publication Year: 2013 , Page(s): 1025 - 1038
    Cited by:  Papers (3)
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    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1381 KB) |  | HTML iconHTML  

    In this paper, we consider the problem of learning from multiple related tasks for improved generalization performance by extracting their shared structures. The alternating structure optimization (ASO) algorithm, which couples all tasks using a shared feature representation, has been successfully applied in various multitask learning problems. However, ASO is nonconvex and the alternating algorit... View full abstract»

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  • Algorithms for 3D Shape Scanning with a Depth Camera

    Publication Year: 2013 , Page(s): 1039 - 1050
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (6121 KB) |  | HTML iconHTML  

    We describe a method for 3D object scanning by aligning depth scans that were taken from around an object with a Time-of-Flight (ToF) camera. These ToF cameras can measure depth scans at video rate. Due to comparably simple technology, they bear potential for economical production in big volumes. Our easy-to-use, cost-effective scanning solution, which is based on such a sensor, could make 3D scan... View full abstract»

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  • An Incremental DPMM-Based Method for Trajectory Clustering, Modeling, and Retrieval

    Publication Year: 2013 , Page(s): 1051 - 1065
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1672 KB)  

    Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of traje... View full abstract»

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  • Hough Forest Random Field for Object Recognition and Segmentation

    Publication Year: 2013 , Page(s): 1066 - 1079
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2539 KB) |  | HTML iconHTML  

    This paper presents a new computational framework for detecting and segmenting object occurrences in images. We combine Hough forest (HF) and conditional random field (CRF) into HFRF to assign labels of object classes to image regions. HF captures intrinsic and contextual properties of objects. CRF then fuses the labeling hypotheses generated by HF for identifying every object occurrence. Interact... View full abstract»

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  • Inverse Rendering of Faces with a 3D Morphable Model

    Publication Year: 2013 , Page(s): 1080 - 1093
    Cited by:  Papers (2)
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    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1885 KB) |  | HTML iconHTML  

    In this paper, we present a complete framework to inverse render faces with a 3D Morphable Model (3DMM). By decomposing the image formation process into geometric and photometric parts, we are able to state the problem as a multilinear system which can be solved accurately and efficiently. As we treat each contribution as independent, the objective function is convex in the parameters and a global... View full abstract»

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  • Joint Depth Map and Color Consistency Estimation for Stereo Images with Different Illuminations and Cameras

    Publication Year: 2013 , Page(s): 1094 - 1106
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (6771 KB) |  | HTML iconHTML  

    In this paper, we propose a method that infers both accurate depth maps and color-consistent stereo images for radiometrically varying stereo images. In general, stereo matching and performing color consistency between stereo images are a chicken-and-egg problem since it is not a trivial task to simultaneously achieve both goals. Hence, we have developed an iterative framework in which these two p... View full abstract»

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  • Learning a Confidence Measure for Optical Flow

    Publication Year: 2013 , Page(s): 1107 - 1120
    Cited by:  Papers (4)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2787 KB) |  | HTML iconHTML  

    We present a supervised learning-based method to estimate a per-pixel confidence for optical flow vectors. Regions of low texture and pixels close to occlusion boundaries are known to be difficult for optical flow algorithms. Using a spatiotemporal feature vector, we estimate if a flow algorithm is likely to fail in a given region. Our method is not restricted to any specific class of flow algorit... View full abstract»

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  • Learning Topic Models by Belief Propagation

    Publication Year: 2013 , Page(s): 1121 - 1134
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1917 KB) |  | HTML iconHTML  

    Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interest and touches on many important applications in text mining, computer vision and computational biology. This paper represents the collapsed LDA as a factor graph, which enables the classic loopy belief propagation (BP) algorithm for approximate inference a... View full abstract»

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  • Linear Dependency Modeling for Classifier Fusion and Feature Combination

    Publication Year: 2013 , Page(s): 1135 - 1148
    Cited by:  Papers (4)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1697 KB) |  | HTML iconHTML  

    This paper addresses the independent assumption issue in fusion process. In the last decade, dependency modeling techniques were developed under a specific distribution of classifiers or by estimating the joint distribution of the posteriors. This paper proposes a new framework to model the dependency between features without any assumption on feature/classifier distribution, and overcomes the dif... View full abstract»

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  • Local Evidence Aggregation for Regression-Based Facial Point Detection

    Publication Year: 2013 , Page(s): 1149 - 1163
    Cited by:  Papers (9)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2328 KB)  

    We propose a new algorithm to detect facial points in frontal and near-frontal face images. It combines a regression-based approach with a probabilistic graphical model-based face shape model that restricts the search to anthropomorphically consistent regions. While most regression-based approaches perform a sequential approximation of the target location, our algorithm detects the target location... View full abstract»

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  • Multiscale Local Phase Quantization for Robust Component-Based Face Recognition Using Kernel Fusion of Multiple Descriptors

    Publication Year: 2013 , Page(s): 1164 - 1177
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2289 KB) |  | HTML iconHTML  

    Face recognition subject to uncontrolled illumination and blur is challenging. Interestingly, image degradation caused by blurring, often present in real-world imagery, has mostly been overlooked by the face recognition community. Such degradation corrupts face information and affects image alignment, which together negatively impact recognition accuracy. We propose a number of countermeasures des... View full abstract»

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  • Online Feature Selection with Streaming Features

    Publication Year: 2013 , Page(s): 1178 - 1192
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2508 KB) |  | HTML iconHTML  

    We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observat... View full abstract»

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  • Partial Face Recognition: Alignment-Free Approach

    Publication Year: 2013 , Page(s): 1193 - 1205
    Cited by:  Papers (15)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1647 KB) |  | HTML iconHTML  

    Numerous methods have been developed for holistic face recognition with impressive performance. However, few studies have tackled how to recognize an arbitrary patch of a face image. Partial faces frequently appear in unconstrained scenarios, with images captured by surveillance cameras or handheld devices (e.g., mobile phones) in particular. In this paper, we propose a general partial face recogn... View full abstract»

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  • Self-Calibration of Catadioptric Camera with Two Planar Mirrors from Silhouettes

    Publication Year: 2013 , Page(s): 1206 - 1220
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1801 KB) |  | HTML iconHTML  

    If an object is interreflected between two planar mirrors, we may take an image containing both the object and its multiple reflections, i.e., simultaneously imaging multiple views of an object by a single pinhole camera. This paper emphasizes the problem of recovering both the intrinsic and extrinsic parameters of the camera using multiple silhouettes from one single image. View pairs among views... View full abstract»

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  • Simultaneous Registration of Multiple Images: Similarity Metrics and Efficient Optimization

    Publication Year: 2013 , Page(s): 1221 - 1233
    Cited by:  Papers (2)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (712 KB) |  | HTML iconHTML  

    We address the alignment of a group of images with simultaneous registration. Therefore, we provide further insights into a recently introduced framework for multivariate similarity measures, referred to as accumulated pair-wise estimates (APE), and derive efficient optimization methods for it. More specifically, we show a strict mathematical deduction of APE from a maximum-likelihood framework an... View full abstract»

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  • Spatially Varying Color Distributions for Interactive Multilabel Segmentation

    Publication Year: 2013 , Page(s): 1234 - 1247
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (10215 KB) |  | HTML iconHTML  

    We propose a method for interactive multilabel segmentation which explicitly takes into account the spatial variation of color distributions. To this end, we estimate a joint distribution over color and spatial location using a generalized Parzen density estimator applied to each user scribble. In this way, we obtain a likelihood for observing certain color values at a spatial coordinate. This lik... View full abstract»

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  • Tracking People's Hands and Feet Using Mixed Network AND/OR Search

    Publication Year: 2013 , Page(s): 1248 - 1262
    Cited by:  Papers (2)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (14806 KB) |  | HTML iconHTML  

    We describe a framework that leverages mixed probabilistic and deterministic networks and their AND/OR search space to efficiently find and track the hands and feet of multiple interacting humans in 2D from a single camera view. Our framework detects and tracks multiple people's heads, hands, and feet through partial or full occlusion; requires few constraints (does not require multiple views, hig... View full abstract»

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  • Unified Detection and Tracking of Instruments during Retinal Microsurgery

    Publication Year: 2013 , Page(s): 1263 - 1273
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1027 KB) |  | HTML iconHTML  

    Methods for tracking an object have generally fallen into two groups: tracking by detection and tracking through local optimization. The advantage of detection-based tracking is its ability to deal with target appearance and disappearance, but it does not naturally take advantage of target motion continuity during detection. The advantage of local optimization is efficiency and accuracy, but it re... View full abstract»

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  • Schroedinger Eigenmaps for the Analysis of Biomedical Data

    Publication Year: 2013 , Page(s): 1274 - 1280
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (820 KB) |  | HTML iconHTML  

    We introduce Schroedinger Eigenmaps (SE), a new semi-supervised manifold learning and recovery technique. This method is based on an implementation of graph Schroedinger operators with appropriately constructed barrier potentials as carriers of labeled information. We use our approach for the analysis of standard biomedical datasets and new multispectral retinal images. View full abstract»

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  • [Back inside cover]

    Publication Year: 2013 , Page(s): c3
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  • [Back cover]

    Publication Year: 2013 , Page(s): c4
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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.

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Meet Our Editors

Editor-in-Chief
David A. Forsyth
University of Illinois