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Space-time isosurface evolution for temporally coherent 3D reconstruction

Space-time isosurface evolution for temporally coherent 3D r...

引用

conference on computer vision and pattern recognition (cvpr)

作者： B. Goldluecke M. Magnor Graphics-Optics-Vision Max Planck Institut für Informatik Saarbruecken Germany

We model the dynamic geometry of a time-varying scene as a 3D isosurface in space-time. The intersection of the isosurface with planes of constant time yields the geometry at a single time instant. An optimal fit of our model to multiple video sequences is defined as the minimum of an energy functional. This functional is given by an integral over the entire hypersurface, which is designed to optimize photo-consistency. A PDE-based evolution derived from the Euler-Lagrange equation maximizes consistency with all of the given video data simultaneously. The result is a 3D model of the scene which varies smoothly over time. The geometry reconstructed by this scheme is significantly better than results obtained by space-carving approaches that do not enforce temporal coherence.

关键词： Isosurfaces Layout Image reconstruction Geometry Surface reconstruction Solid modeling Level set Rendering (computer graphics) Video sequences Equations

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Radiometric alignment of image sequences

Radiometric alignment of image sequences

引用

conference on computer vision and pattern recognition (cvpr)

作者： Seon Joo Kim M. Pollefeys Department of Computer Science North Carolina State University Chapel Hill NC USA

Color values in an image are related to image irradiance by a nonlinear function called radiometric response function. Since this function depends on the aperture and the shutter speed, image intensity of a same object may vary during the acquisition of an image sequence due to auto exposure feature of the camera. While this is desirable to make optimal use of the limited dynamic range of most cameras, this causes problems for a number of applications in computer vision. In this paper we propose a method for estimating the radiometric response function and apply it to radiometrically align images so that the color values are consistent for all images of a sequence. Our approach computes the response function, exposure and white balance changes between images (up to some ambiguity) for a moving camera without any prior knowledge about exposures. We show the performance of our algorithm by estimating the response function from synthetic images and also from real world data, using it to radiometrically align the images.

关键词： Radiometry Image sequences Layout Dynamic range computer vision Brightness Shape measurement Application software Digital cameras Iterative algorithms

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A fast multigrid implicit algorithm for the evolution of geodesic active contours

A fast multigrid implicit algorithm for the evolution of geo...

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conference on computer vision and pattern recognition (cvpr)

作者： G. Papandreou P. Maragos School of Electrical and Computer Engin National and Technical University of Athens Athens Greece

Active contour models are among the most popular PDE-based tools in computer vision. In this paper we present a new algorithm for the fast evolution of geodesic active contours and compare it with other established numerical schemes. The new algorithm employs a full time-implicit and unconditionally stable numerical scheme and applies multigrid methods for the efficient solution of the occurring sparse linear system. When we utilize very big time-steps for the numerical evolution of the front, the proposed scheme has increased accuracy and better rotational invariance properties compared with the alternative AOS scheme. This allows for the rapid evolution and convergence of the contour to its final configuration after only very few iterations. Standard pyramidal and/or narrowband techniques can be easily integrated into our algorithm and further accelerate the curve evolution. Experimental results in object boundary detection demonstrate the power of the method.

关键词： Active contours computer vision Object detection Level set Geophysics computing Narrowband Solid modeling Stability Multigrid methods Linear systems

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Camera network calibration from dynamic silhouettes

Camera network calibration from dynamic silhouettes

引用

conference on computer vision and pattern recognition (cvpr)

作者： S.N. Sinha M. Pollefeys L. McMillan Department of Computer Science University of North Carolina Chapel Hill USA

In this paper we present an automatic method for calibrating a network of cameras from only silhouettes. This is particularly useful for shape-from-silhouette or visual-hull systems, as no additional data is needed for calibration. The key novel contribution of this work is an algorithm to robustly compute the epipolar geometry from dynamic silhouettes. We use the fundamental matrices computed by this method to determine the projective reconstruction of the complete camera configuration. This is refined into a metric reconstruction using self-calibration. We validate our approach by calibrating a four camera visual-hull system from archive data where the dynamic object is a moving person. Once the calibration parameters have been computed, we use a visual-hull algorithm to reconstruct the dynamic object from its silhouettes.

关键词： Cameras Calibration Shape Image reconstruction Video sequences Robustness Computational geometry computer science Layout Humans

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Inferring 3D body pose from silhouettes using activity manifold learning

Inferring 3D body pose from silhouettes using activity manif...

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conference on computer vision and pattern recognition (cvpr)

作者： A. Elgammal Chan-Su Lee Department of Computer Science Rutgers University New Brunswick NJ USA

We aim to infer 3D body pose directly from human silhouettes. Given a visual input (silhouette), the objective is to recover the intrinsic body configuration, recover the viewpoint, reconstruct the input and detect any spatial or temporal outliers. In order to recover intrinsic body configuration (pose) from the visual input (silhouette), we explicitly learn view-based representations of activity manifolds as well as learn mapping functions between such central representations and both the visual input space and the 3D body pose space. The body pose can be recovered in a closed form in two steps by projecting the visual input to the learned representations of the activity manifold, i.e., finding the point on the learned manifold representation corresponding to the visual input, followed by interpolating 3D pose.

关键词： Humans Image reconstruction Motion analysis Solid modeling Kinematics Cameras computer science Surveillance Biological system modeling Geometry

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Parts-based 3D object classification

Parts-based 3D object classification

引用

conference on computer vision and pattern recognition (cvpr)

作者： D. Huber A. Kapuria R. Donamukkala M. Hebert The Robotics Institute Carnegie Mellon University Pittsburgh PA USA

This paper presents a parts-based method for classifying scenes of 3D objects into a set of pre-determined object classes. Working at the part level, as opposed to the whole object level, enables a more flexible class representation and allows scenes in which the query object is significantly occluded to be classified. In our approach, parts are extracted from training objects and grouped into part classes using a hierarchical clustering algorithm. Each part class is represented as a collection of semi-local shape features and can be used to perform pan class recognition. A mapping from part classes to object classes is derived from the learned part classes and known object classes. At run-time, a 3D query scene is sampled, local shape features are computed, and the object class is determined using the learned pan classes and the pan-to-object mapping. Classifying novel 3D scenes of vehicles into eight classes demonstrate the approach.

关键词： Layout Object recognition Shape Vehicles computer vision Robots Clustering algorithms Runtime Laser modes computer society

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Simultaneous calibration and tracking with a network of non-overlapping sensors

Simultaneous calibration and tracking with a network of non-...

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conference on computer vision and pattern recognition (cvpr)

作者： A. Rahimi B. Dunagan T. Darrell Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA

We describe a method for simultaneously recovering the trajectory of a target and the external calibration parameters of non-overlapping cameras in a multi-camera system. Each camera is assumed to measure the location of a moving target within its field of view with respect to the camera's ground-plane coordinate system. Calibrating the network of cameras requires aligning each camera's ground-plane coordinate system with a global ground-plane coordinate system. Prior knowledge about the target's dynamics can compensate for the lack of overlap between the camera fields of view. The target is allowed to move freely with varying speed and direction. We demonstrate the idea with a network of indoor wireless cameras.

关键词： Calibration Cameras Target tracking Trajectory Intelligent sensors Wireless sensor networks Extrapolation Sensor phenomena and characterization Sensor systems computer science

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Brightness perception, dynamic range and noise: a unifying model for adaptive image sensors

Brightness perception, dynamic range and noise: a unifying m...

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conference on computer vision and pattern recognition (cvpr)

作者： V. Brajovic Carnegie Mellon University USA

Many computer vision applications have to cope with large dynamic range and changing illumination conditions in the environment. Any attempt to deal with these conditions at the algorithmic level alone are inherently difficult because of the following: (1) conventional image sensors cannot completely capture wide dynamic range radiances without saturation or underexposure; (2) the quantization process destroys small signal variations especially in shadows; and (3) all possible illumination conditions cannot be completely accounted for. The paper proposes a computational model for brightness perception that deals with issues of dynamic range and noise. The model can be implemented on-chip in analog domain before the signal is saturated or destroyed through quantization. The model is "unified" because a single mathematical formulation addresses the problem of shot and thermal noise, and normalizes the signal range to simultaneously compress the dynamic range, minimize appearance variations due to changing illumination, and minimize quantization noise. The model strongly mimics brightness perception processes in early biological vision.

关键词： Brightness Dynamic range Image sensors Lighting Quantization Biological system modeling Working environment noise computer vision Application software Signal processing

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Local smoothing for manifold learning

Local smoothing for manifold learning

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conference on computer vision and pattern recognition (cvpr)

作者： JinHyeong Park Zhenyue Zhang Hongyuan Zha R. Kasturi Department of Computer Science and Engineering Pennsylvania State University USA Department of Mathematics University of Zhejiang Hangzhou China Department of Computer Science and Engineering University of South Florida USA

We propose methods for outlier handling and noise reduction using weighted local linear smoothing for a set of noisy points sampled from a nonlinear manifold. Weighted PCA is used as a building block for our methods and we suggest an iterative weight selection scheme for robust local linear fitting together with an outlier detection method based on minimal spanning trees to further improve robustness. We also develop an efficient and effective bias-reduction method to deal with the "trim the peak and fill the valley" phenomenon in local linear smoothing. Synthetic examples along with several image data sets are presented to show that manifold learning methods combined with weighted local linear smoothing give more accurate results.

关键词： Smoothing methods Noise reduction computer vision Principal component analysis Learning systems Manifolds computer science Application software Independent component analysis Nearest neighbor searches

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A GMM parts based face representation for improved verification through relevance adaptation

A GMM parts based face representation for improved verificat...

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conference on computer vision and pattern recognition (cvpr)

作者： S. Lucey Tsuhan Chen Advanced Multimedia Processing Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

Motivated by the success of parts based representations in face detection we have attempted to address some of the problems associated with applying such a philosophy to the task of face verification. Hitherto, a major problem with this approach in face verification is the intrinsic lack of training observations, stemming from individual subjects, in order to estimate the required conditional distributions. The estimated distributions have to be generalized enough to encompass the differing permutations of a subject's face yet still be able to discriminate between subjects. In our work the well known Gaussian mixture model (GMM) framework is employed to model the conditional density function of the parts based representation of the face. We demonstrate that excellent performance can be obtained from our GMM based representation through the employment of adaptation theory, specifically relevance adaptation (RA). Our results are presented for the frontal images of the BANCA database.

关键词： Face detection pattern recognition Image sequences Laboratories Density functional theory Employment Image databases Robustness Image analysis pattern analysis

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