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Attribute Augmentation with Sparse Coding 22

Attribute Augmentation with Sparse Coding

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22nd International conference on Pattern Recognition (ICPR)

作者： Wang, Xiaoyang Ji, Qiang Rensselaer Polytech Inst Dept Elect Comp & Syst Engn Troy NY 12180 USA

ISBN: (纸本)9781479952083

This work proposes a novel sparse coding based approach for augmenting attributes in both object recognition and facial expression recognition applications. Attributes are a set of manually specified binary descriptions of visual objects. Though playing an important role in different applications like zero-shot learning, image description and recognition, the manually specified attributes suffer from the incomplete capturing of the original image data. In this work, we propose to augment the original manually specified semantic attributes with the augmented attributes which are also sparse, based on the minimization of the reconstruction error between the original image and the concatenated semantic and augmented attributes. We propose to iteratively learn the dictionaries as well as recover the augmented attributes in the optimization. For our applications of object recognition and facial expression recognition, the augmented attributes combined with the predicted semantic attributes can improve the overall recognition rate. Also, our learned dictionaries show certain meanings captured by the attributes.

关键词： Dictionaries Encoding Equations Face recognition Object recognition Optimization Semantics Dictionaries as Topic object recognition Semantics Facial Recognition Sparse coding reconstruction error original image image description image data Manual handling

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Aerial reconstructions via Probabilistic data Fusion 27

Aerial Reconstructions via Probabilistic Data Fusion

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27th IEEE conference on Computer Vision and Pattern Recognition (CVPR)

作者： Cabezas, Randi Freifeld, Oren Rosman, Guy Fisher, John W., iii MIT Cambridge MA 02139 USA

ISBN: (纸本)9781479951178

We propose an integrated probabilistic model for multi-modal fusion of aerial imagery, LiDAR data, and (optional) GPS measurements. The model allows for analysis and dense reconstruction (in terms of both geometry and appearance) of large 3D scenes. An advantage of the approach is that it explicitly models uncertainty and allows for missing data. As compared with image-based methods, dense reconstructions of complex urban scenes are feasible with fewer observations. Moreover, the proposed model allows one to estimate absolute scale and orientation, and reason about other aspects of the scene, e.g., detection of moving objects. As formulated, the model lends itself to massively-parallel computing. We exploit this in an efficient inference scheme that utilizes both general purpose and domain-specific hardware components. We demonstrate results on large-scale reconstruction of urban terrain from LiDAR and aerial photography data.

关键词： Bayesian inference aerial lidar reconstruction structure from motion

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3D Spine reconstruction of Postoperative Patients from Multi-level Manifold Ensembles

3D Spine Reconstruction of Postoperative Patients from Multi...

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17th International conference on Medical image Computing and Computer-Assisted Intervention (MICCAI)

作者： Kadoury, Samuel Labelle, Hubert Parent, Stefan Polytech Montreal Med Montreal PQ Canada Sainte Justine Hosp Res Ctr Montreal PQ Canada

ISBN: (纸本)9783319104430;9783319104423

The quantitative assessment of surgical outcomes using personalized anatomical models is an essential task for the treatment of spinal deformities such as adolescent idiopathic scoliosis. However an accurate 3D reconstruction of the spine from postoperative X-ray images remains challenging due to presence of instrumentation (metallic rods and screws) occluding vertebrae on the spine. In this paper, we formulate the reconstruction problem as an optimization over a manifold of articulated spine shapes learned from pathological training data. The manifold itself is represented using a novel data structure, a multi-level manifold ensemble, which contains links between nodes in a single hierarchical structure, as well as links between different hierarchies, representing overlapping partitions. We show that this data structure allows both efficient localization and navigation on the manifold, for on-the-fly building of local nonlinear models (manifold charting). Our reconstruction framework was tested on pre- and postoperative X-ray datasets from patients who underwent spinal surgery. Compared to manual ground-truth, our method achieves a 3D reconstruction accuracy of 2.37 +/- 0.85mm for postoperative spine models and can deal with severe cases of scoliosis.

关键词： data structures

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Updating a preoperative surface model with information from real-time tracked 2D ultrasound using a Poisson surface reconstruction algorithm

Updating a preoperative surface model with information from ...

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conference on Medical Imaging - image-Guided Procedures, Robotic Interventions, and Modeling

作者： Sun, Deyu Rettmann, Maryam E. Holmes, David R., iii Linte, Cristian A. Packer, Douglas Robb, Richard A. Mayo Clin Biomed Imaging Resources Rochester MN 55905 USA Mayo Clin Div Cardiovasc Dis Rochester MN 55905 USA Rochester Inst Technol Ctr Imaging Sci Biomed Engn Rochester NY 14623 USA

ISBN: (纸本)9780819498298

In this work, we propose a method for intraoperative reconstruction of a left atrial surface model for the application of cardiac ablation therapy. In this approach, the intraoperative point cloud is acquired by a tracked, 2D freehand intra-cardiac echocardiography device, which is registered and merged with a preoperative, high resolution left atrial surface model built from computed tomography data. For the surface reconstruction, we introduce a novel method to estimate the normal vector of the point cloud from the preoperative left atrial model, which is required for the Poisson Equation reconstruction algorithm. In the current work, the algorithm is evaluated using a preoperative surface model from patient computed tomography data and simulated intraoperative ultrasound data. Factors such as intraoperative deformation of the left atrium, proportion of the left atrial surface sampled by the ultrasound, sampling resolution, sampling noise, and registration error were considered through a series of simulation experiments.

关键词： intraoperative left atrial surface reconstruction normal vector estimation Poisson Equation reconstruction intra-cardiac echocardiography

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THE APPLICATION OF DICTIONARY BASED COMPRESSED SENSING FOR PHOTOACOUSTIC image 13

THE APPLICATION OF DICTIONARY BASED COMPRESSED SENSING FOR P...

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International conference on Machine Learning and Cybernetics

作者： Zhou, Lili Wang, Jiajun Hu, Danfeng Soochow Univ Sch Elect & Informat Engn Suzhou Peoples R China

ISBN: (纸本)9781479942152

Restrictions of the hardware conditions and spatial size usually limit the number of the measurements in photo acoustic imaging which will finally degrade the quality of the reconstructed image with the back projection algorithm. In order to recover larger number of measurements from incomplete ones, a compressed sensing (CS) based method was proposed. Different from most existed CS-based photoacoustic reconstruction method, the transform matrix for converting the measurement data to their compressed version is obtained by learning a dictionary with the K-SVD method. Visual assessment and quantitative evaluations in terms of the mean squared error (MSE) and the peak signal-to-noise ratio (PSNR) demonstrate the superiorities of our proposed method.

关键词： Photoacoustic image Compressed sensing K-SVD Dictionary learning

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Is Compressive Sensing really Useful for Radar?

Is Compressive Sensing really Useful for Radar?

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IEEE Radar conference - from Sensing to Information

作者： Kemkemian, Stephane Nouvel-Fiani, Myriam Thales Airborne Syst Sensors Syst Tech Directorate Elancourt France

ISBN: (纸本)9781479920358

Compressive Sensing (CS) was originally developed to directly acquire a compressed description of a sparse scene. This can be possible provided that the sampling scheme meet certain criteria. In Radar applications, the main advantage highlighted in the literature is the reduction of the data-flow between the R.F. front-end and processing that would be intractable in number of cases. However thanks to the technological progresses in fast Analog to Digital Conversion (ADC) and subsequent digital processing, the real problem is not at this level except in some special cases. The real issue is that it is not always possible to sample the radar signal ideally for practical and uncontrollable reasons. So far, most of the work in the literature has focused on the mathematical aspect of the underlying L1 inverse problem. This paper shows some examples where the use of sparse or incomplete sampling is really justified. We also show that the inverse problem resolution based on the minimization of the L1 norm, even if it is elegant way to solve the problem, is not the only means to address the problem.

关键词： image reconstruction Noise Radar imaging Sensors Synthetic aperture radar Vectors Inverse method Synthetic aperture radar Cloning Vectors radar image reconstruction front-ends Sensors Noise Analog-digital conversion Radar applications Compressed sensing Radar imaging

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image tag completion by low-rank factorization with dual reconstruction structure preserved

Image tag completion by low-rank factorization with dual rec...

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作者： Li, Xue Zhang, Yu-Jin Shen, Bin Liu, Bao-Di Electronic Engineering Tsinghua University Beijing100084 China Computer Science Purdue University West LafayetteIN47907 United States Information and Control Engineering China University of Petroleum Qingdao266580 China

ISBN: (纸本)9781479957514

A novel tag completion algorithm is proposed in this paper, which is designed with the following features: 1) Low-rank and error s-parsity: the incomplete initial tagging matrix D is decomposed into the complete tagging matrix A and a sparse error matrix E. However, instead of minimizing its nuclear norm, A is further factorized into a basis matrix U and a sparse coefficient matrix V, i.e. D = UV + E. This low-rank formulation encapsulating sparse coding enables our algorithm to recover latent structures from noisy initial data and avoid performing too much denoising;2) Local reconstruction structure consistency: to steer the completion of D, the local linear reconstruction structures in feature space and tag space are obtained and preserved by U and V respectively. Such a scheme could alleviate the negative effect of distances measured by low-level features and incomplete tags. Thus, we can seek a balance between exploiting as much information and not being mislead to suboptimal performance. Experiments conducted on Corel5k dataset and the newly issued Flickr30Concepts dataset demonstrate the effectiveness and efficiency of the proposed method. © 2014 IEEE.

关键词： Errors

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Registration of Building Intensity image and Its Color image Using SIFT Algorithm 3

Registration of Building Intensity image and Its Color Image...

引用

3rd International conference on Civil, Architectural and Hydraulic Engineering (ICCAHE)

作者： Cang, Guihua Yue, Jianping Hohai Univ Sch Earth Sci & Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9783038352587

Fusion of close range photogrammetry (CRP) and terrestrial laser scanning (TLS) technology has been a hot topic in the field of building reconstruction. There are many ways to realize the fusion of the two kind data. In this paper, we propose a method for 3D-2D data registration based on Scale Invariant Feature Transform (SIFT) algorithm and range intensity data. 3D terrestrial laser scanner and digital camera are different sensors, which will lead to large difference between intensity image (derived from range intensity data) and color image. The traditional image matching method can not apply to register these kind images. This paper focuses on studying the feasibility and practicability of SIFT algorithm on such different images matching. The result shows that the principal of SIFT method is suitable for the registration of the two kind images.

关键词： image Registration Terrestrial Laser Scanning Intensity image Color image SIFT Algorithm

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Experimental study of super-resolution using a compressive sensing architecture 3

Experimental study of super-resolution using a compressive s...

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conference on Compressive Sensing iii

作者： Flake, J. Christopher Euliss, Gary Greer, John B. Shubert, Stephanie Easley, Glenn Gemp, Kevin Baptista, Brian Stenner, Michael D. Sallee, Phil A. Natl Geospatial Intelligence Agcy 7500 Geoint Dr Springfield VA 22150 USA Mitre Corp Mclean VA 22102 USA Booz Allen Hamilton Mclean VA 22102 USA

ISBN: (纸本)9781628410464

An experimental investigation of super-resolution imaging from measurements of projections onto a random basis is presented. In particular, a laboratory imaging system was constructed following an architecture that has become familiar from the theory of compressive sensing. The system uses a digital micromirror array located at an intermediate image plane to introduce binary matrices that represent members of a basis set. The system model was developed from experimentally acquired calibration data which characterizes the system output corresponding to each individual mirror in the array. images are reconstructed at a resolution limited by that of the micromirror array using the split Bregman approach to total-variation regularized optimization. System performance is evaluated qualitatively as a function of the size of the basis set, or equivalently, the number of snapshots applied in the reconstruction.

关键词： Sensors Digital micromirror devices Super resolution Mirrors image resolution Compressed sensing Binary data Cameras Charge-coupled devices Imaging systems

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6th Pacific-Rim Symposium on image and Video Technology, PSIVT 2013 with GCCV 2013, GPID 2013, PAESNPR 2013, and QACIVA 2013

6th Pacific-Rim Symposium on Image and Video Technology, PSI...

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6th Pacific-Rim Symposium on image and Video Technology, PSIVT 2013 with GCCV 2013, GPID 2013, PAESNPR 2013, and QACIVA 2013

ISBN: (纸本)9783642539251

The proceedings contain 23 papers. The special focus in this conference is image and video technology. The topics include: Inverse Skeletal strokes;animated non-photorealistic rendering in multiple styles;rating image aesthetics using a crowd sourcing approach;length estimation for exponential parameterization and Ε-uniform samplings;accuracy of rajectories estimation in a driver-assistance context;digital convexity and cavity trees;efficient reconstruction of complex 3-D scenes from incomplete RGB-D data;fotonic and electron microscopy images for quality evaluation of delignification of agave fibers;description of the enzymatic browning in avocado slice using GLCM image texture;image preprocessing assessment detecting low contrast regions under non-homogeneous light conditions;an approach for utility pole recognition in real conditions;morphological analysis for temporary behaviour description of photoelasticity images on plastic films;least square for grassmann-cayley agelbra in homogeneous coordinates;harmonic flow for histogram matching;medical image segmentation using multi-level set partitioning with topological graph prior;initializing 3-D reconstruction from three views using three fundamental matrices;a new a contrario approach for the robust determination of the fundamental matrix;regression based trajectory learning and prediction for human motion;local affine optical flow computation;performance of image registration and its extensions for interpolation of facial motion and Discrete Rigid Transformation Graph Search for 2D image Registration.

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