journal
MENU ▼
Read by QxMD icon Read
search

IEEE Transactions on Pattern Analysis and Machine Intelligence

journal
https://www.readbyqxmd.com/read/27893385/nelasso-group-sparse-modeling-for-characterizing-relations-among-named-entities-in-news-articles
#1
Amara Tariq, Asim Karim, Hassan Foroosh
Named entities such as people, locations, and organizations play a vital role in characterizing online content. They often reflect information of interest and are frequently used in search queries. Although named entities can be detected reliably from textual content, extracting relations among them is more challenging, yet useful in various applications (e.g. news recommending systems). In this paper, we present a novel model and system for learning semantic relations among named entities from collections of news articles...
November 23, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27893384/recovering-inner-slices-of-layered-translucent-objects-by-multi-frequency-illumination
#2
Kenichiro Tanaka, Yasuhiro Mukaigawa, Hiruyuki Kubo, Yasuyuki Matsushita, Yasushi Yagi
This paper describes a method for recovering appearance of inner slices of translucent objects. The appearance of a layered translucent object is the summed appearance of all layers, where each layer is blurred by a depth-dependent point spread function (PSF). By exploiting the difference of low-pass characteristics of depth-dependent PSFs, we develop a multi-frequency illumination method for obtaining the appearance of individual inner slices. Specifically, by observing the target object with varying the spatial frequency of checker-pattern illumination, our method recovers the appearance of inner slices via computation...
November 23, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27893383/efficient-globally-optimal-consensus-maximisation-with-tree-search
#3
Tat-Jun Chin, Pulak Purkait, Anders Eriksson, David Suter
Maximum consensus is one of the most popular criteria for robust estimation in computer vision. Despite its widespread use, optimising the criterion is still customarily done by randomised sample-and-test techniques, which do not guarantee optimality of the result. Several globally optimal algorithms exist, but they are too slow to challenge the dominance of randomised methods. Our work aims to change this state of affairs by proposing an efficient algorithm for global maximisation of consensus. Under the framework of LP-type methods, we show how consensus maximisation for a wide variety of vision tasks can be posed as a tree search problem...
November 23, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27893382/a-new-framework-for-quality-assessment-of-high-resolution-fingerprint-images
#4
Raoni Teixeira, Neucimar Leite
The quality assessment of sets of features extracted from patterns of epidermal ridges on our fingers is a biometric challenge problem with implications on questions concerning security, privacy and identity fraud. In this work, we introduced a new methodology to analyze the quality of high-resolution fingerprint images containing sets of fingerprint pores. Our approach takes into account the spatial interrelationship between the considered features and some basic transformations involving point process and anisotropic analysis...
November 22, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27875216/image-registration-and-change-detection-under-rolling-shutter-motion-blur
#5
Vijay Rengarajan, Ambasamudram Narayanan Rajagopalan, Rangarajan Aravind, Guna Seetharaman
In this paper, we address the problem of registering a distorted image and a reference image of the same scene by estimating the camera motion that had caused the distortion. We simultaneously detect the regions of changes between the two images. We attend to the coalesced effect of rolling shutter and motion blur that occurs frequently in moving CMOS cameras. We first model a general image formation framework for a 3D scene following a layered approach in the presence of rolling shutter and motion blur. We then develop an algorithm which performs layered registration to detect changes...
November 18, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27875215/local-submodularization-for-binary-pairwise-energies
#6
Lena Gorelick, Yuri Boykov, Olga Veksler, Ismail Ben Ayed, Andrew Delong
Many computer vision problems require optimization of binary non-submodular energies. We propose a general optimization framework based on local submodular approximations (LSA). Unlike standard LP relaxation methods that linearize the whole energy globally, our approach iteratively approximates the energy locally. On the other hand, unlike standard local optimization methods (e.g., gradient descent or projection techniques) we use non-linear submodular approximations and optimize them without leaving the domain of integer solutions...
November 18, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27875213/on-the-latent-variable-interpretation-in-sum-product-networks
#7
Robert Peharz, Robert Gens, Franz Pernkopf, Pedro Domingos
One of the central themes in Sum-Product networks (SPNs) is the interpretation of sum nodes as marginalized latent variables (LVs). This interpretation yields an increased syntactic or semantic structure, allows the application of the EM algorithm and to efficiently perform MPE inference. In literature, the LV interpretation was justified by explicitly introducing the indicator variables corresponding to the LVs' states. However, as pointed out in this paper, this approach is in conflict with the completeness condition in SPNs and does not fully specify the probabilistic model...
November 18, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27849524/building-proteins-in-a-day-efficient-3d-molecular-structure-estimation-with-electron-cryomicroscopy
#8
Ali Punjani, Marcus Brubaker, David Fleet
Discovering the 3D atomic-resolution structure of molecules such as proteins and viruses is one of the foremost research problems in biology and medicine. Electron Cryomicroscopy (cryo-EM) is a promising vision-based technique for structure estimation which attempts to reconstruct 3D atomic structures from a large set of 2D transmission electron microscope images. This paper presents a new Bayesian framework for cryo-EM structure estimation that builds on modern stochastic optimization techniques to allow one to scale to very large datasets...
November 10, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27849523/videostory-embeddings-recognize-events-when-examples-are-scarce
#9
Amirhossein Habibian, Thomas Mensink, Cees G M Snoek
This paper aims for event recognition when video examples are scarce or even completely absent. The key in such a challenging setting is a semantic video representation. Rather than building the representation from individual attribute detectors and their annotations, we propose to learn the entire representation from freely available web videos and their descriptions using an embedding between video features and term vectors. In our proposed embedding, which we call Video2vec, the correlations between the words are utilized to learn a more effective representation by optimizing a joint objective balancing descriptiveness and predictability...
November 10, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27845653/non-stationary-rician-noise-estimation-in-parallel-mri-using-a-single-image-a-variance-stabilizing-approach
#10
Tomasz Pieciak, Santiago Aja-Fernandez, Gonzalo Vegas Sanchez-Ferrero
Parallel magnetic resonance imaging (pMRI) techniques have gained a great importance both in research and clinical communities recently since they considerably accelerate the image acquisition process. However, the image reconstruction algorithms needed to correct the subsampling artifacts affect the nature of noise, i.e. it becomes non-stationary. Some methods have been proposed in the literature dealing with the non-stationary noise in pMRI. However, their performance depends on information not usually available such as multiple acquisitions, receiver noise matrices, sensitivity coil profiles, reconstruction coefficients, or even biophysical models of the data...
November 7, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27831860/estimating-cortical-feature-maps-with-dependent-gaussian-processes
#11
Nicholas J Hughes, Geoffrey J Goodhill
A striking example of brain organisation is the stereotyped arrangement of cell preferences in the visual cortex for edges of particular orientations in the visual image. These "orientation preference maps" appear to have remarkably consistent statistical properties across many species. However fine scale analysis of these properties requires the accurate reconstruction of maps from imaging data which is highly noisy. A new approach for solving this reconstruction problem is to use Bayesian Gaussian process methods, which produce more accurate results than classical techniques...
November 2, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27875214/visual-vibrometry-estimating-material-properties-from-small-motions-in-video
#12
Abe Davis, Katherine L Bouman, Justin G Chen, Michael Rubinstein, Oral Buyukozturk, Fredo Durand, William T Freeman
The estimation of material properties is important for scene understanding, with many applications in vision, robotics, and structural engineering. This paper connects fundamentals of vibration mechanics with computer vision techniques in order to infer material properties from small, often imperceptible motion in video. Objects tend to vibrate in a set of preferred modes. The frequencies of these modes depend on the structure and material properties of an object. We show that by extracting these frequencies from video of a vibrating object, we can often make inferences about that object's material properties...
November 1, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27831859/shape-and-spatially-varying-reflectance-estimation-from-virtual-exemplars
#13
Zhuo Hui, Aswin C Sankaranarayanan
This paper addresses the problem of estimating the shape of objects that exhibit spatially-varying reflectance. We assume that multiple images of the object are obtained under a fixed view-point and varying illumination, i.e., the setting of photometric stereo. At the core of our techniques is the assumption that the BRDF at each pixel lies in the non-negative span of a known BRDF dictionary. This assumption enables a per-pixel surface normal and BRDF estimation framework that is computationally tractable and requires no initialization in spite of the underlying problem being non-convex...
November 1, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27831858/visual-vibrometry-estimating-material-properties-from-small-motions-in-video
#14
Abe Davis, Katherine Bouman, Justin Chen, Michael Rubinstein, Oral Buyukozturk, Fredo Durand, William Freeman
The estimation of material properties is important for scene understanding, with many applications in vision, robotics, and structural engineering. This paper connects fundamentals of vibration mechanics with computer vision techniques in order to infer material properties from small, often imperceptible motion in video. Objects tend to vibrate in a set of preferred modes. The frequencies of these modes depend on the structure and material properties of an object. We show that by extracting these frequencies from video of a vibrating object, we can often make inferences about that object's material properties...
November 1, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27810800/evaluation-of-segmentation-quality-via-adaptive-composition-of-reference-segmentations
#15
Bo Peng, Lei Zhang, Xuanqin Mou, Ming-Hsuan Yang
Evaluating image segmentation quality is a critical step for generating desirable segmented output and comparing performance of algorithms, among others. However, automatic evaluation of segmented results is inherently challenging since image segmentation is an ill-posed problem. This paper presents a framework to evaluate segmentation quality using multiple labeled segmentations which are considered as references. For a segmentation to be evaluated, we adaptively compose a reference segmentation using multiple labeled segmentations, which locally matches the input segments while preserving structural consistency...
October 27, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27810799/real-time-enhancement-of-dynamic-depth-videos-with-non-rigid-deformations
#16
Kassem Al Ismaeil, Djamila Aouada, Thomas Solignac, Bruno Mirbach, Bjorn Ottersten
We propose a novel approach for enhancing depth videos containing non-rigidly deforming objects. Depth sensors are capable of capturing depth maps in real-time but suffer from high noise levels and low spatial resolutions. While solutions for reconstructing 3D details in static scenes, or scenes with rigid global motions have been recently proposed, handling unconstrained non-rigid deformations in relative complex scenes remains a challenge. Our solution consists in a recursive dynamic multi-frame super-resolution algorithm where the relative local 3D motions between consecutive frames are directly accounted for...
October 27, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27810798/learning-to-recognize-human-activities-using-soft-labels
#17
Ninghang Hu, Gwenn Englebienne, Zhongyu Lou, Ben Krose
Human activity recognition system is of great importance in robot-care scenarios. Typically, training such a system requires activity labels to be both completely and accurately annotated. In this paper, we go beyond such restriction and propose a learning method that allow labels to be incomplete and uncertain. We introduce the idea of soft labels which allows annotators to assign multiple, and weighted labels to data segments. This is very useful in many situations, e.g., when the labels are uncertain, when part of the labels are missing, or when multiple annotators assign inconsistent labels...
October 26, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27810797/video-object-discovery-and-co-segmentation-with-extremely-weak-supervision
#18
Le Wang, Gang Hua, Rahul Sukthankar, Jianru Xue, Zhenxing Niu, Nanning Zheng
We present a spatio-temporal energy minimization formulation for simultaneous video object discovery and co-segmentation across multiple videos containing irrelevant frames. Our approach overcomes a limitation that most existing video co-segmentation methods possess, i.e., they perform poorly when dealing with practical videos in which the target objects are not present in many frames. Our formulation incorporates a spatio-temporal auto-context model, which is combined with appearance modeling for superpixel labeling...
October 26, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27775512/learn-on-source-refine-on-target-a-model-transfer-learning-framework-with-random-forests
#19
Noam Segev, Maayan Harel, Shie Mannor, Koby Crammer, Ran El-Yaniv
We propose novel model transfer-learning methods that refine a decision forest model M learned within a "source" domain using a training set sampled from a "target" domain, assumed to be a variation of the source. We present two random forest transfer algorithms. The first algorithm searches greedily for locally optimal modifications of each tree structure by trying to locally expand or reduce the tree around individual nodes. The second algorithm does not modify structure, but only the parameter (thresholds) associated with decision nodes...
October 18, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27740475/patchmatch-filter-edge-aware-filtering-meets-randomized-search-for-visual-correspondence
#20
Jiangbo Lu, Yu Li, Hongsheng Yang, Dongbo Min, Weiyong Eng, Minh Do
Though many tasks in computer vision can be formulated elegantly as pixel-labeling problems, a typical challenge discouraging such a discrete formulation is often due to computational efficiency. Recent studies on fast cost volume filtering based on efficient edge-aware filters provide a fast alternative to solve discrete labeling problems, with the complexity independent of the support window size. However, these methods still have to step through the entire cost volume exhaustively, which makes the solution speed scale linearly with the label space size...
October 11, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
journal
journal
34134
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"