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Fully automatic registration of 3D point clouds

Fully automatic registration of 3D point clouds

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Makadia, Ameesh Patterson IV, Alexander Daniilidis, Kostas Department of Computer and Information Science University of Pennsylvania Philadelphia PA 19104 United States

ISBN: (纸本)0769525970

We propose a novel technique for the registration of 3D point clouds which makes very few assumptions: we avoid any manual rough alignment or the use of landmarks, displacement can be arbitrarily large, and the two point sets can have very little overlap. Crude alignment is achieved by estimation of the 3D-rotation from two Extended Gaussian Images even when the data sets inducing them have partial overlap. The technique is based on the correlation of the two EGIs in the Fourier domain and makes use of the spherical and rotational harmonic transforms. For pairs with low overlap which fail a critical verification step, the rotational alignment can be obtained by the alignment of constellation images generated from the EGIs. Rotationally aligned sets are matched by correlation using the Fourier transform of volumetric functions. A fine alignment is acquired in the final step by running Iterative Closest Points with just few iterations. © 2006 ieee.

关键词： pattern recognition

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Face recognition using 2.5D shape information

Face recognition using 2.5D shape information

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Smith, William A. P. Hancock, Edwin R. Department of Computer Science University of York

ISBN: (纸本)0769525970

In this paper we investigate whether the 2.5D shape information delivered by a novel shape-from-shading algorithm can be used for illumination insensitive face recognition. We present a robust and efficient facial shape-from-shading algorithm which uses principal geodesic analysis to model the variation in surface orientation across a face. We show how this algorithm can be used to recover accurate facial shape and albedo from real world images. Our second contribution is to use the recovered 2.5D shape information in a variety of recognition methods. We present a novel recognition strategy in which similarity is measured in the space of the principal geodesic parameters. We also use the recovered shape information to generate illumination normalised prototype images on which recognition can be performed. Finally we show that, from a single input image, we are able to generate the basis images employed by a number of well known illumination-insensitive recognition algorithms. We also demonstrate that the principal geodesics provide an efficient parameterisation of the space of harmonic basis images. © 2006 ieee.

关键词： Face recognition

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Privacy & security issues related to match scores

Privacy & security issues related to match scores

引用

2006 conference on computer vision and pattern recognition workshops

作者： Mohanty, Pranab Sarkar, Sudeep Kasturi, Rangachar Computer Science and Engineering University of South Florida Tampa FL 33620 United States

ISBN: (纸本)0769526462

Security and privacy issues remains a major hurdle in wide deployment of biometric based authentication system. For example, unauthorized access or regeneration of face templates has serious implications on the privacy of the concerned users. For robust and practical implementation of such system, it is necessary to identify and explore the possible ways by which reconstruction of template is feasible. In this paper, we show that even match scores carries sufficient information for reconstruction of the original face templates. We propose a novel non-iterative scheme to reconstruct face templates from match scores. We use an affine transformation of the images to approximate the behavior of a given face recognition system using an independent set of face templates termed as "break-in" set. Selected templates from the break-in set are matched only once with the enrolled template of the target account and match scores are recorded. These scores are then embedded in the approximating affine space along with break-in set templates to compute the co-ordinates of the target template. The inverse transformation is used to reconstruct the original target template. We present the reconstruction of templates for a commercial off the shelf (COTS) face recognition system. The COTS system is set to operate at 1% False Acceptance Rate and 99% True Acceptance Rate with 100 enrollments. We observed that with proposed scheme, at most 450 attempts are required to achieve a 0.93 probability of break into the COTS face recognition system by choosing a random gallery target. © 2006 ieee.

关键词： Electronic document identification systems

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Accelerated kernel feature analysis

Accelerated kernel feature analysis

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Xianhua, Jiang Snapp, Robert R. Yuichi, Motai Xingquan, Zhu Dept. of Electrical and Computer Engineering Dept. of Computer Science University of Vermont Burlington VT 05405

ISBN: (纸本)0769525970

A fast algorithm, Accelerated Kernel Feature Analysis (AKFA), that discovers salient features evidenced in a sample of n unclassified patterns, is presented. Like earlier kernel-based feature selection algorithms, AKFA implicitly embeds each pattern into a Hubert space, H, induced by a Mercer kernel. An -dimensional linear subspace of H is iteratively constructed by maximizing a variance condition for the nonlinearly transformed sample. This linear subspace can then be used to define more efficient data representations and pattern classifiers. AKFA requires O(/n2) operations, as compared to O(n3) for Schölkof, Smola, and Müller's Kernel Principal Component Analysis (KPCA), and O(2n2) for Smola, Mangasarian, and Schölkopf's Sparse Kernel Feature Analysis (SKFA). Numerical experiments show that AKFA can generate more concise feature representations than both KPCA and SKFA, and demonstrate that AKFA obtains similar classification performance as KPCA for a face recognition problem. © 2006 ieee.

关键词： Feature extraction

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Graph Laplacian kernels for object classification from a single example

Graph Laplacian kernels for object classification from a sin...

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Chang, Hong Yeung, Dit-Yan Department of Computer Science Hong Kong University of Science and Technology

ISBN: (纸本)0769525970

Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this problem in the context of specific applications, very little work has been done so far on the problem under more general object classification settings. In this paper, we propose a graph-based approach to the problem. Based on a robust path-based similarity measure proposed recently, we construct a weighted graph using the robust path-based similarities as edge weights. A kernel matrix, called graph Laplacian kernel, is then defined based on the graph Laplacian. With the kernel matrix, in principle any kernel-based classifier can be used for classification. In particular, we demonstrate the use of a kernel nearest neighbor classifier on some synthetic data and real-world image sets, showing that our method can successfully solve some difficult classification tasks with only very few labeled examples. © 2006 ieee.

关键词： Graph theory

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A framework for feature selection for background subtraction

A framework for feature selection for background subtraction

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Parag, Toufiq Elgammal, Ahmed Mittal, Anurag Dept. of Computer Science Rutgers University Piscataway NJ 08854 Real-time Vision and Modeling Dept. Siemens Corporate Research Princeton NJ 08540 Dept. of Computer Science and Automatic Control University of Alexandria Egypt Dept. of Computer Science and Engg IIT Madras Chennai India

ISBN: (纸本)0769525970

Background subtraction is a widely used paradigm to detect moving objects in video taken from a static camera and is used for various important applications such as video surveillance, human motion analysis, etc. Various statistical approaches have been proposed for modeling a given scene background. However, there is no theoretical framework for choosing which features to use to model different regions of the scene background. In this paper we introduce a novel framework for feature selection for background modeling and subtraction. A boosting algorithm, namely RealBoost, is used to choose the best combination of features at each pixel. Given the probability estimates from a pool of features calculated by Kernel Density Estimate (KDE) over a certain time period, the algorithm selects the most useful ones to discriminate foreground objects from the scene background. The results show that the proposed framework successfully selects appropriate features for different parts of the image. © 2006 ieee.

关键词： Object recognition

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Applying ensembles of multilinear classifiers in the frequency domain

Applying ensembles of multilinear classifiers in the frequen...

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Bauckhage, Christian Käster, Thomas Tsotsos, John K. Deutsche Telekom Laboratories 10587 Berlin Germany Centre for Vision Research York University Toronto Ont. M3J1P3 Canada

ISBN: (纸本)0769525970

Ensemble methods such as bootstrap, bagging or boosting have had a considerable impact on recent developments in machine learning, pattern recognition and computer vision. Theoretical and practical results alike have established that, in terms of accuracy, ensembles of weak classifiers generally outperform monolithic solutions. However, this comes at the cost of an extensive training process. The work presented in this paper results from projects on advanced human machine interaction. In scenarios like ours, online learning is a major requirement, and lengthy training is prohibitive. We therefore propose a different approach to ensemble learning. Instead of a set of weak classifiers, we combine strong, separable, multilinear discriminant functions. These are especially suited for computer vision: they train very quickly and allow for rapid classification of image content. Training different classifiers for different contexts or on semantically organized data provides ensembles of experts. We collapse a set of experts into a single multilinear function and thus achieve the same runtime for arbitrarily many classifiers as for a single one. Moreover, carrying out the classification in the frequency domain results in faster frame rates. Experiments with image sequences recorded in typical home environments show that our ensemble training schemes yield high accuracy on unconstrained and cluttered data. © 2006 ieee.

关键词： Classification (of information)

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The design of high-level features for photo quality assessment

The design of high-level features for photo quality assessme...

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Ke, Yan Tang, Xiaoou Jing, Feng School of Computer Science Carnegie Mellon Microsoft Research Asia

ISBN: (纸本)0769525970

We propose a principled method for designing high level features for photo quality assessment. Our resulting system can classify between high quality professional photos and low quality snapshots. Instead of using the bag of low-level features approach, we first determine the perceptual factors that distinguish between professional photos and snapshots. Then, we design high level semantic features to measure the perceptual differences. We test our features on a large and diverse dataset and our system is able to achieve a classification rate of 72% on this difficult task. Since our system is able to achieve a precision of over 90% in low recall scenarios, we show excellent results in a web image search application. © 2006 ieee.

关键词： Feature extraction

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3D alignment of face in a single image

3D alignment of face in a single image

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Gu, Lie Kanade, Takeo Computer Science Department Carnegie Mellon University

ISBN: (纸本)0769525970

We present an approach for aligning a 3D deformable model to a single face image. The model consists of a set of sparse 3D points and the view-based patches associated with every point. Assuming a weak perspective projection model, our algorithm iteratively deforms the model and adjusts the 3D pose to fit the image. As opposed to previous approaches, our algorithm starts the fitting without resorting to manual labeling of key facial points. And it makes no assumptions about global illumination or surface properties, so it can be applied to a wide range of imaging conditions. Experiments demonstrate that our approach can effectively handle unseen faces with a variety of pose and illumination variations. © 2006 ieee.

关键词： Three dimensional

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Image completion using global optimization

Image completion using global optimization

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Komodakis, Nikos Tziritas, Georgios Computer Science Department University of Crete

ISBN: (纸本)0769525970

A new exemplar-based framework unifying image completion, texture synthesis and image inpainting is presented in this work. Contrary to existing greedy techniques, these tasks are posed in the form of a discrete global optimization problem with a well defined objective function. For solving this problem a novel optimization scheme, called Priority-BP, is proposed which carries two very important extensions over standard belief propagation (BP): "priority-based message scheduling" and "dynamic label pruning". These two extensions work in cooperation to deal with the intolerable computational cost of BP caused by the huge number of existing labels. Moreover, both extensions are generic and can therefore be applied to any MRF energy function as well. The effectiveness of our method is demonstrated on a wide variety of image completion examples. © 2006 ieee.

关键词： Image processing

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