# IEEE Transactions on Pattern Analysis and Machine Intelligence

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Displaying Results 1 - 19 of 19

Publication Year: 2015, Page(s): C1
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• ### IEEE Transactions on Pattern Analysis and Machine Intelligence Editorial Board

Publication Year: 2015, Page(s): C2
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• ### A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type

Publication Year: 2015, Page(s):489 - 498
Cited by:  Papers (3)
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Advantages of model-based clustering methods over heuristic alternatives have been widely demonstrated in the literature. Most model-based clustering algorithms assume that the data are either discrete or continuous, possibly allowing both types to be present in separate features. In this paper, we introduce a model-based approach for clustering feature vectors of mixed type, allowing each feature... View full abstract»

• ### A Contrario 2D Point Alignment Detection

Publication Year: 2015, Page(s):499 - 512
Cited by:  Papers (8)
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In spite of many interesting attempts, the problem of automatically finding alignments in a 2D set of points seems to be still open. The difficulty of the problem is illustrated here by very simple examples. We then propose an elaborate solution. We show that a correct alignment detection depends on not less than four interlaced criteria, namely the amount of masking in texture, the relative bilat... View full abstract»

• ### A Statistical Analysis of IrisCode and Its Security Implications

Publication Year: 2015, Page(s):513 - 528
Cited by:  Papers (4)
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IrisCode has been used to gather iris data for 430 million people. Because of the huge impact of IrisCode, it is vital that it is completely understood. This paper first studies the relationship between bit probabilities and a mean of iris images (The mean of iris images is defined as the average of independent iris images.) and then uses the Chi-square statistic, the correlation coefficient and a... View full abstract»

• ### Convolutional Sparse Coding for Trajectory Reconstruction

Publication Year: 2015, Page(s):529 - 540
Cited by:  Papers (35)
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Trajectory basis Non-Rigid Structure from Motion (NRSfM) refers to the process of reconstructing the 3D trajectory of each point of a non-rigid object from just their 2D projected trajectories. Reconstruction relies on two factors: (i) the condition of the composed camera & trajectory basis matrix, and (ii) whether the trajectory basis has enough degrees of freedom to model the 3D point trajectory... View full abstract»

• ### Dense Subgraph Partition of Positive Hypergraphs

Publication Year: 2015, Page(s):541 - 554
Cited by:  Papers (2)
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In this paper, we present a novel partition framework, called dense subgraph partition (DSP), to automatically, precisely and efficiently decompose a positive hypergraph into dense subgraphs. A positive hypergraph is a graph or hypergraph whose edges, except self-loops, have positive weights. We first define the concepts of core subgraph, conditional core subgraph, and disjoint partition of a cond... View full abstract»

• ### Detection and Rectification of Distorted Fingerprints

Publication Year: 2015, Page(s):555 - 568
Cited by:  Papers (8)
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Elastic distortion of fingerprints is one of the major causes for false non-match. While this problem affects all fingerprint recognition applications, it is especially dangerous in negative recognition applications, such as watchlist and deduplication applications. In such applications, malicious users may purposely distort their fingerprints to evade identification. In this paper, we proposed no... View full abstract»

• ### Global Contrast Based Salient Region Detection

Publication Year: 2015, Page(s):569 - 582
Cited by:  Papers (350)
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Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed... View full abstract»

• ### High-Speed Tracking with Kernelized Correlation Filters

Publication Year: 2015, Page(s):583 - 596
Cited by:  Papers (431)
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The core component of most modern trackers is a discriminative classifier, tasked with distinguishing between the target and the surrounding environment. To cope with natural image changes, this classifier is typically trained with translated and scaled sample patches. Such sets of samples are riddled with redundancies—any overlapping pixels are constrained to be the same. Based on this sim... View full abstract»

• ### Learning Image Descriptors with Boosting

Publication Year: 2015, Page(s):597 - 610
Cited by:  Papers (24)
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We propose a novel and general framework to learn compact but highly discriminative floating-point and binary local feature descriptors. By leveraging the boosting-trick we first show how to efficiently train a compact floating-point descriptor that is very robust to illumination and viewpoint changes. We then present the main contribution of this paper—a binary extension o... View full abstract»

• ### Minimum Cost Multi-Way Data Association for Optimizing Multitarget Tracking of Interacting Objects

Publication Year: 2015, Page(s):611 - 624
Cited by:  Papers (15)
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This paper presents a general formulation for a minimum cost data association problem which associates data features via one-to-one, m-to-one and one-to-n links with minimum total cost of the links. A motivating example is a problem of tracking multiple interacting nanoparticles imaged on video frames, where particles can aggregate into one particle or a particle can be split into multiple particl... View full abstract»

• ### Non-Rigid Graph Registration Using Active Testing Search

Publication Year: 2015, Page(s):625 - 638
Cited by:  Papers (11)
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We present a new approach for matching sets of branching curvilinear structures that form graphs embedded in ${\mathbb {R}}^2$ or ${\mathbb {R}}^3$ View full abstract»

• ### Probabilistic Common Spatial Patterns for Multichannel EEG Analysis

Publication Year: 2015, Page(s):639 - 653
Cited by:  Papers (28)
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Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed frame... View full abstract»

• ### Skeletonization and Partitioning of Digital Images Using Discrete Morse Theory

Publication Year: 2015, Page(s):654 - 666
Cited by:  Papers (12)
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We show how discrete Morse theory provides a rigorous and unifying foundation for defining skeletons and partitions of grayscale digital images. We model a grayscale image as a cubical complex with a real-valued function defined on its vertices (the voxel values). This function is extended to a discrete gradient vector field using the algorithm presented in Robins, Wood, Sheppard TPAMI 33:1646 (20... View full abstract»

• ### Static Signature Synthesis: A Neuromotor Inspired Approach for Biometrics

Publication Year: 2015, Page(s):667 - 680
Cited by:  Papers (15)
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In this paper we propose a new method for generating synthetic handwritten signature images for biometric applications. The procedures we introduce imitate the mechanism of motor equivalence which divides human handwriting into two steps: the working out of an effector independent action plan and its execution via the corresponding neuromuscular path. The action plan is represented as a trajectory... View full abstract»

• ### Towards Contactless, Low-Cost and Accurate 3D Fingerprint Identification

Publication Year: 2015, Page(s):681 - 696
Cited by:  Papers (11)
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Human identification using fingerprint impressions has been widely studied and employed for more than 2000 years. Despite new advancements in the 3D imaging technologies, widely accepted representation of 3D fingerprint features and matching methodology is yet to emerge. This paper investigates 3D representation of widely employed 2D minutiae features by recovering and incorporating (i) min... View full abstract»

• ### IEEE Transactions on Pattern Analysis and Machine Intelligence Information for Authors

Publication Year: 2015, Page(s): C3
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• ### IEEE Computer Society

Publication Year: 2015, 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.

Full Aims & Scope

## Meet Our Editors

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