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Combined depth and outlier estimation in multi-view stereo

Combined depth and outlier estimation in multi-view stereo

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

作者： Strecha, Christoph Fransens, Rik Van Gool, Luc K.U.Leuven-ESAT-Psi Kasteelpark 1 3001 Leuven Belgium

ISBN: (纸本)0769525970

In this paper, we present a generative model based approach to solve the multi-view stereo problem. The input images are considered to be generated by either one of two processes: (i) an inlier process, which generates the pixels which are visible from the reference camera and which obey the constant brightness assumption, and (ii) an outlier process which generates all other pixels. Depth and visibility are jointly modelled as a hidden Markov Random Field, and the spatial correlations of both are explicitly accounted for. Inference is made tractable by an EM-algorithm, which alternates between estimation of visibility and depth, and optimisation of model parameters. We describe and compare two implementations of the E-step of the algorithm, which correspond to the Mean Field and Bethe approximations of the free energy. The approach is validated by experiments on challenging real-world scenes, of which two are contaminated by independently moving objects. © 2006 ieee.

关键词： Stereo vision

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3D facial expression recognition based on primitive surface feature distribution

3D facial expression recognition based on primitive surface ...

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

作者： Wang, Jun Yin, Lijun Wei, Xiaozhou Sun, Yi Department of Computer Science State University of New York Binghamton NY 13902 United States

ISBN: (纸本)0769525970

The creation of facial range models by 3D imaging systems has led to extensive work on 3D face recognition [19]. However, little work has been done to study the usefulness of such data for recognizing and understanding facial expressions. Psychological research shows that the shape of a human face, a highly mobile facial surface, is critical to facial expression perception. In this paper, we investigate the importance and usefulness of 3D facial geometric shapes to represent and recognize facial expressions using 3D facial expression range data. We propose a novel approach to extract primitive 3D facial expression features, and then apply the feature distribution to classify the prototypic facial expressions. In order to validate our proposed approach, we have conducted experiments for person-independent facial expression recognition using our newly created 3D facial expression database. We also demonstrate the advantages of our 3D geometric based approach over 2D texture based approaches in terms of various head poses. © 2006 ieee.

关键词： Face recognition

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Inferring facial action units with causal relations

Inferring facial action units with causal relations

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

作者： Tong, Yan Liao, Wenhui Ji, Qiang Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180-3590 United States

ISBN: (纸本)0769525970

A system that could automatically analyze the facial actions in real time have applications in a number of different fields. However, developing such a system is always a challenging task due to the richness, ambiguity, and dynamic nature of facial actions. Although a number of research groups attempt to recognize action units (AUs) by either imp roving facial feature extraction techniques, or the AU classification techniques, these methods often recognize AUs individually and statically, therefore ignoring the semantic relationships among AUs and the dynamics of AUs. Hence, these approaches cannot always recognize AUs reliably, robustly, and consistently. In this paper, we propose a novel approach for AUs classification, that systematically accounts for relationships among AUs and their temporal evolution. Specifically, we use a dynamic Bayesian network (DBN) to model the relationships among different AUs. The DBN provides a coherent and unified hierarchical probabilistic framework to represent probabilistic relationships among different AUs and account for the temporal changes in facial action development. Under our system, robust computer vision techniques are used to get AU measurements. And such AU measurements are then applied as evidence into the DBN for inferencing various AUs. The experiments show the integration of AU relationships and AU dynamics with AU image measurements yields significant improvements in AU recognition. © 2006 ieee.

关键词： Face recognition

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3D surface matching and recognition using conformal geometry

3D surface matching and recognition using conformal geometry

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

作者： Wang, Sen Wang, Yang Jin, Miao Gu, Xianfeng Samaras, Dimitris State University of New York at Stony Brook Computer Science Department Stony Brook NY 11794 United States

ISBN: (纸本)0769525970

3D surface matching is a fundamental issue in computer vision with many applications such as shape registration, 3D object recognition and classification. However, surface matching with noise, occlusion and clutter is a challenging problem. In this paper, we analyze a family of conformal geometric maps including harmonic maps, conformal maps and least squares conformal maps with regards to 3D surface matching. As a result, we propose a novel and computationally efficient surface matching framework that uses least squares conformal maps. According to conformal geometry theory, each 3D surface with disk topology can be mapped to a 2D domain through a global optimization and the resulting map is a diffeomorphism, i.e., one-to-one and onto. This allows us to simplify the 3D surface-matching problem to a 2D image-matching problem, by comparing the resulting 2D conformal geometric maps, which are stable, insensitive to resolution changes and robust to occlusion and noise. Therefore, highly accurate and efficient 3D surface matching algorithms can be achieved by using conformal geometric maps. Finally, the performance of conformal geometric maps is evaluated and analyzed comprehensively in 3D surface matching with occlusion, noise and resolution variation. We also provide a series of experiments on real 3D face data that achieve high recognition rates. © 2006 ieee.

关键词： pattern matching

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Reconstructing occluded surfaces using synthetic apertures: Stereo, focus and robust measures

Reconstructing occluded surfaces using synthetic apertures: ...

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

作者： Vaish, Vaibhav Szeliski, Richard Zitnick, C.L. Kang, Sing Bing Levoy, Marc Computer Science Department Stanford University CA Microsoft Research Redmond WA

ISBN: (纸本)0769525970

Most algorithms for 3D reconstruction from images use cost functions based on SSD, which assume that the surfaces being reconstructed are visible to all cameras. This makes it difficult to reconstruct objects which are partially occluded. Recently, researchers working with large camera arrays have shown it is possible to "see through" occlusions using a technique called synthetic aperture focusing. This suggests that we can design alternative cost functions that are robust to occlusions using synthetic apertures. Our paper explores this design space. We compare classical shape from stereo with shape from synthetic aperture focus. We also describe two variants of multi-view stereo based on color medians and entropy that increase robustness to occlusions. We present an experimental comparison of these cost functions on complex light fields, measuring their accuracy against the amount of occlusion. © 2006 ieee.

关键词： Image reconstruction

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Interactive feature tracking using K-D trees and dynamic programming

Interactive feature tracking using K-D trees and dynamic pro...

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

作者： Buchanan, Aeron Fitzgibbon, Andrew Dept. Engineering Science University of Oxford United Kingdom Microsoft Research Cambridge United Kingdom

ISBN: (纸本)0769525970

A new approach to template tracking is presented, incorporating three distinct contributions. Firstly, an explicit definition for a feature track is given. Secondly, the advantages of an image preprocessing stage are demonstrated and, in particular, the effectiveness of highly compressed image patch data stored in k-d trees for fast and discriminatory image patch searches. Thirdly, the k-d trees are used to generate multiple track hypotheses which are efficiently merged to give the optimal solution using dynamic programming. The explicit separation of feature detection and trajectory determination creates the basis for the novel use of k-d trees and dynamic programming. Multiple appearances and occlusion handling are seamlessly integrated into this framework. Appearance variation through the sequence is robustly handled in an iterative process. The work presented is a significant foundation for a powerful off-line feature tracking system, particularly in the context of interactive applications. © 2006 ieee.

关键词： Interactive computer systems

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An adaptive appearance model approach for model-based articulated object tracking

An adaptive appearance model approach for model-based articu...

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

作者： BǍlan, Alexandra O. Black, Michael J. Department of Computer Science Brown University Providence RI 02912 United States

ISBN: (纸本)0769525970

The detection and tracking of three-dimensional human body models has progressed rapidly but successful approaches typically rely on accurate foreground silhouettes obtained using background segmentation. There are many practical applications where such information is imprecise. Here we develop a new image likelihood function based on the visual appearance of the subject being tracked. We propose a robust, adaptive, appearance model based on the Wandering-Stable-Lost framework extended to the case of articulated body parts. The method models appearance using a mixture model that includes an adaptive template, frame-to-frame matching and an outlier process. We employ an annealed particle filtering algorithm for inference and take advantage of the 3D body model to predict self-occlusion and improve pose estimation accuracy. Quantitative tracking results are presented for a walking sequence with a 180 degree turn, captured with four synchronized and calibrated cameras and containing significant appearance changes and self-occlusion in each view. © 2006 ieee.

关键词： Object recognition

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An integrated model of top-down and bottom-up attention for optimizing detection speed

An integrated model of top-down and bottom-up attention for ...

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

作者： Navalpakkam, Vidhya Itti, Laurent Dept. of Computer Science Neuroscience Graduate Program University of Southern California

ISBN: (纸本)0769525970

Integration of goal-driven, top-down attention and image-driven, bottom-up attention is crucial for visual search. Yet, previous research has mostly focused on models that are purely top-down or bottom-up. Here, we propose a new model that combines both. The bottom-up component computes the visual salience of scene locations in different feature maps extracted at multiple spatial scales. The top-down component uses accumulated statistical knowledge of the visual features of the desired search target and background clutter, to optimally tune the bottom-up maps such that target detection speed is maximized. Testing on 750 artificial and natural scenes shows that the model's predictions are consistent with a large body of available literature on human psychophysics of visual search. These results suggest that our model may provide good approximation of how humans combine bottom-up and top-down cues such as to optimize target detection speed. © 2006 ieee.

关键词： Search engines

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A shape representation for planar curves by shape signature harmonic embedding

A shape representation for planar curves by shape signature ...

引用

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

作者： Lee, Sang-Mook Abbott, A. Lynn Clark, Neil A. Araman, Philip A. Electrical and Computer Engineering Virginia Tech. Blacksburg VA 24061 United States SRS-4702 USDA Forest Service Blacksburg VA 24060 United States

ISBN: (纸本)0769525970

This paper introduces a new representation for planar curves, From the well-known Dirichlet problem for a disk, the harmonic function embedded in a circular disk is solely dependent on specified boundary values and can be obtained from Poisson's integral formula. We derive a discrete version of Poisson's formula and assess its harmonic properties. Various shape signatures can be used as boundary values, whereas only the corresponding Fourier descriptors are needed for the framework. The proposed approach is similar to a scale space representation but exhibits greater generality by accommodating using any type of shape signature. In addition, it is robust to noise and computationally efficient, and it is guaranteed to have a unique solution. In this paper, we demonstrate that the approach has strong potential for shape representation and matching applications. © 2006 ieee.

关键词： Computational geometry

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Joint boosting feature selection for robust face recognition

Joint boosting feature selection for robust face recognition

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

作者： Xiao, Rong Li, Wujun Tian, Yuandong Tang, Xiaoou Microsoft Research Asia Beijing 100080 China National Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai 200030 China

ISBN: (纸本)0769525970

A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framework is proposed to address this problem. In our framework, 3D face models are used to synthesize a huge database of realistic face images which covers wide appearance variations of faces due to various pose, illumination, and expression changes. A novel feature selection algorithm which we call Joint Boosting is developed to extract discriminative face features using this massive database. The major contributions of this paper are: (1) With the help of 3D face models, a massive database of realistic virtual face images is generated to achieve robust feature selection;(2)Because the huge database covers a wide range of face variations, our feature selection procedure only needs to be trained once, and the selected feature set can be generalized to other face database without re-training;(3) We propose a new learning algorithm, Joint Boosting Algorithm, which is effective and efficient in learning directly from a massive database without having to convert face images to intra-personal and extra-personal difference images. This property is important for applying our algorithm to other general pattern recognition problems. Experimental results show that our method significantly improves recognition performance. © 2006 ieee.

关键词： Face recognition

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