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检索条件"任意字段=3rd International Symposium on 3D Data Processing, Visualization, and Transmission, 3DPVT 2006"

共 148 条记录，以下是131-140 订阅

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Illumination Insensitive Model-Based 3d Object Tracking and Texture Refinement

Illumination Insensitive Model-Based 3D Object Tracking and ...

引用

international symposium on 3d data processing visualization and transmission

作者： Hua Yang Greg Welch Marc Pollefeys Computer Science Department University of North Carolina Chapel Hill Chapel Hill NC USA

A common approach to model-based tracking is to use a model of the object to predict what will be observed, and then to compare that with real observations. For methods that make use of the object's photometric properties (appearance) in their measurements, illumination inconsistencies between the modeled and actual scene can cause tracking problems. In this paper we address one case: model-based tracking of Lambertian objects under directional light sources. We present an iterative optimization method that uses a Kalman filter to simultaneously refine estimates of the object motion, the illumination, and the model texture. We model the illumination variance between the real and predicted observation using the intensity ratios of corresponding surface points, which we then use to make model-based image predictions consistent with the real lighting. To demonstrate the effectiveness of our method we present experimental results using both synthetic (controlled) and real image sequences.

关键词： Lighting Predictive models Image sequences Photometry Layout Solid modeling Graphics Light sources data mining Optical computing

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3d City Modeling Using Cognitive Loops

3D City Modeling Using Cognitive Loops

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international symposium on 3d data processing visualization and transmission

作者： Nico Cornelis Bastian Leibe Kurt Cornelis Luc Van Gool KU Leuven Leuven Belgium ETH Zurich Zurich Switzerland

3d city modeling using computer vision is very challenging. A typical city contains objects which are a nightmare for some vision algorithms, while other algorithms have been designed to identify exactly these parts but, in their turn, suffer from other weaknesses which limit their application. For instance, moving cars with metallic surfaces can degrade the results of a 3d city reconstruction algorithm which is primarily based on the assumption of a static scene with diffuse reflection properties. On the other hand, a specialized object recognition algorithm could be able to detect cars, but also yields too many false positives without the availability of additional scene knowledge. In this paper, the design of a cognitive loop which intertwines both aforementioned algorithms is demonstrated for 3d city modeling, proving that the whole can be much more than the simple sum of its parts. A cognitive loop is the mutual transfer of higher knowledge between algorithms, which enables the combination of algorithms to overcome the weaknesses of any single algorithm. We demonstrate the promise of this approach on a real-world city modeling task using video data recorded by a survey vehicle. Our results show that the cognitive combination of algorithms delivers convincing city models which improve upon the degree of realism that is possible from a purely reconstruction-based approach.

关键词： Cities and towns Algorithm design and analysis Object recognition Layout Computer vision Application software Surface reconstruction degradation Reconstruction algorithms Reflection

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EKF-Based Recursive dual Estimation of Structure & Motion from Stereo data

EKF-Based Recursive Dual Estimation of Structure & Motion fr...

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international symposium on 3d data processing visualization and transmission

作者： Hongsheng Zhang Shahriar Negahdaripour Underwater Vision and Imaging Laboratory Electrical and Computer Engineering Department University of Miami Coral Gables FL USA

Extended Kalman filters (EKF) have been proposed to estimate ego-motion and to recursively update scene structure in the form of 3-d positions of selected prominent features from motion and stereo sequences. Previous methods typically accommodate no more than a few dozen features for real-time processing. To maintain motion estimation accuracy, this calls for high contrast images to compute image feature locations with precision. Within manmade environments, various prominent corner points exist that can be extracted and tracked with required accuracy. However, prominent features are more difficult to localize precisely in natural scenes. Statistically, more feature points become necessary to maintain the same level of motion estimation accuracy and robustness. However, this imposes a computational burden beyond the capability of EKF-based techniques for real-time processing. A sequential dual EKF estimator utilizing stereo data is proposed for improved computation efficiency. Two important issues, unbiased estimation and stochastic stability are addressed. Furthermore, the dynamic feature set is handled in a more effective, efficient and robust way. Experimental results to demonstrate the merits of the new theoretical and algorithmic developments are presented.

关键词： Motion estimation Recursive estimation Layout Robustness State estimation Computational efficiency Noise measurement Parameter estimation Laboratories Computer vision

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Motion Parallax without Motion Compensation in 3d Cluttered Scenes

Motion Parallax without Motion Compensation in 3D Cluttered ...

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international symposium on 3d data processing visualization and transmission

作者： M.S. Langer V. Chapdelaine-Couture R. Mann S. Roy School of Computer Science McGill University Montreal QUE Canada School of Computer Science University of Waterloo Waterloo ONT Canada University of Montreal DIRO Montreal QUE Canada

When an observer moves through a rigid 3d scene, points that are near to the observer move with a different image velocity than points that are far away. The difference between image velocity vectors is the direction of motion parallax. This direction vector points towards the observer's translation direction. Hence estimates of the direction of motion parallax are useful for estimating the observer's translation direction. Standard ways to compute the direction of motion parallax either rely on precomputed optical flow, or rely on motion compensation to remove the local image shift caused by observer rotation. Here we present a simple Fourier-based method for estimating the direction of motion parallax directly, that does not require optical flow and motion compensation. The method is real-time and performs accurately for image regions in which multiple motions are present.

关键词： Motion compensation Layout Motion estimation Image motion analysis Optical computing Principal component analysis Computer science Frequency domain analysis

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A Bayesian Approach to Building Footprint Extraction from Aerial LIdAR data

A Bayesian Approach to Building Footprint Extraction from Ae...

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international symposium on 3d data processing visualization and transmission

作者： Oliver Wang Suresh K. Lodha david P. Helmbold University of California Santa Cruz CA USA

Building footprints have been shown to be extremely useful in urban planning, infrastructure development, and roof modeling. Current methods for creating these footprints are often highly manual and rely largely on architectural blueprints or skilled modelers. In this work we use aerial LIdAR data to generate building footprints automatically. Existing automatic methods have been mostly unsuccessful due to large amounts of noise around building edges. We present a novel Bayesian technique for automatically constructing building footprints from a pre-classified LIdAR point cloud. Our algorithm first computes a bounded- error approximate building footprint using an application of the shortest path algorithm. We then determine the most probable building footprint by maximizing the posterior probability using linear optimization and simulated annealing techniques. We have applied our algorithm to more than 300 buildings in our data set and observe that we obtain accurate building footprints compared to the ground truth. Our algorithm is automatic and can be applied to other man-made shapes such as roads and telecommunication lines with minor modifications.

关键词： Bayesian methods data mining Laser radar Buildings Urban planning Clouds Computational modeling Simulated annealing Shape Roads

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Statistical Inference of Biological Structure and Point Spread Functions in 3d Microscopy

Statistical Inference of Biological Structure and Point Spre...

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international symposium on 3d data processing visualization and transmission

作者： Joseph Schlecht Kobus Barnard Barry Pryor Computer Science Department University of Arizona Tucson Tucson AZ USA Plant Sciences Department University of Arizona Tucson Tucson AZ USA

We present a novel method for detecting and quantifying 3d structure in stacks of microscopic images captured at incremental focal lengths. We express the image data as stochastically generated by an underlying model for biological specimen and the effects of the imaging system. The method simultaneously fits a model for proposed structure and the imaging system's parameters, which include a model of the point spread function. We demonstrate our approach by detecting spores in image stacks of Alternaria, a microscopic genus of fungus. The spores are modeled as opaque ellipsoids and fit to the data using statistical inference. Since the number of spores in the data is not known, model selection is incorporated into the fitting process. Thus, we develop a reversible jump Markov chain Monte Carlo sampler to explore the parameter space. Our results show that simultaneous statistical inference of specimen and imaging models is useful for quantifying biological structures in 3d microscopic images. In addition, we show that inferring a model of the imaging system improves the overall fit of the specimen model to the data.

关键词： Biological system modeling Fungi Optical microscopy Optical imaging Biomedical optical imaging Geometrical optics Solid modeling Monte Carlo methods data analysis Biology

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Estimating a-priori Unknown 3d Axially Symmetric Surfaces from Noisy Measurements of Their Fragments

Estimating a-priori Unknown 3D Axially Symmetric Surfaces fr...

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international symposium on 3d data processing visualization and transmission

作者： Andrew Willis david B. Cooper Department of Electrical and Computer Engineering North Carolina State University Charlotte NC USA Division of Engineering Brown University Providence RI USA

In this paper, we present a computationally efficient technique for solving the difficult problem of estimating the global shape of a ceramic pot from measurements of its fragments. Each unknown pot is modeled as a surface of revolution, i.e., a 3d line- the central axis of the pot- and a 2d profile curve with respect to that axis. For each fragment, a probabilistic distribution is estimated which models both the geometric shape of the fragment and the variability of the estimated fragment shape. Estimation of the global pot shape is then a Maximum Likelihood Estimation (MLE) problem where we seek the values of the Euclidean transformation parameters that maximize the joint probability of the matched fragments' axis/profile-curve models (which includes the additional constraint that the matched fragments must share a common central axis). This is a new type of curve-analysis problem and our solution is a new and effective approach applicable for generic constrained 2d curve alignment and for modeling of 3d axially-symmetric surfaces and for comparing geometric models which may correspond over a subset of the complete model.

关键词： Solid modeling Assembly Stochastic processes Shape measurement Maximum likelihood estimation Electric variables measurement Size measurement Noise shaping Ceramics degradation

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Motion Editing in 3d Video database

Motion Editing in 3D Video Database

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international symposium on 3d data processing visualization and transmission

作者： Jianfeng Xu Toshihiko Yamasaki Kiyoharu Aizawa Department of Electronic Engineering University of Tokyo Chiba Japan Department of Frontier Informatics University of Tokyo Kashiwa Chiba Japan The University of Tokyo Japan

As the next generation of media, 3d video is attracting increased attention. 3d video is a sequence of three dimensional mesh models, captured and generated for a real dynamic object. In this paper, we present a simple framework of motion editing in 3d video database to re-use 3d video data. Our system is composed of two modules. In the first module, a motion database is automatically set up from original 3d video sequences off-line by analyzing the feature vectors of each frame. It is observed that our original 3d video sequences have a two-level temporal structure. A fine-to-coarse method is proposed to extract such a structure. 3d video is segmented into the fine-level structure by a three reference frame strategy and then is clustered into the coarse-level structure. In the second module, users can synthesize the motions to edit a new 3d video sequence online. A cost function is optimized to transit between two motions with the users' requirements. All the algorithms in the system are based on the analysis in feature vector space and the edited 3d video sequence is played using OpenGL.

关键词： Video sequences Humans Spatial databases Mesh generation Cameras Shape data engineering Informatics Motion analysis Cost function

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3d Modeling Using Planar Segments and Mesh Elements

3D Modeling Using Planar Segments and Mesh Elements

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international symposium on 3d data processing visualization and transmission

作者： Ioannis Stamos Gene Yu George Wolberg Siavash Zokai Department of Computer Science CUNY New York NY USA Department of Computer Science City College슠of New York New York NY USA Brainstorm Technology New York NY USA

Range sensing technology allows the photorealistic modeling of large-scale scenes, such as urban structures. The generated 3d representations, after automated registration, are useful for urban planning, historical preservation, or virtual reality applications. One major issue in 3d modeling of complex large-scale scenes is that the final result is a dense complicated mesh. Significant, in some cases manual, postprocessing (mesh simplification, hole filling) is required to make this representation usable by graphics or CAd applications. This paper presents a 3d modeling approach that models large planar scene areas of the scene with planar primitives (extracted via a segmentation pre-process), and non-planar areas with mesh primitives. In that respect, the final model is significantly compressed. Also, lines of intersection between neighboring planes are modeled as such. These steps bring the model closer to graphics/CAd applications. We present results from experiments with complex range scans from urban structures and from the interior of a large-scale landmark urban building (Grand Central Terminal, NYC).

关键词： Layout Image segmentation Large-scale systems Filling Laser modes Solid modeling Brain modeling Computer science Educational institutions Urban planning

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Range Image Registration Based on Circular Features

Range Image Registration Based on Circular Features

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international symposium on 3d data processing visualization and transmission

作者： Cecilia Chao Chen Ioannis Stamos Department of Computer Science CUNY New York NY USA

Range sensing technology allows the photo-realistic modeling of large-scale scenes, such as urban structures. A major bottleneck in the process of 3d scene acquisition is the automated registration of a large number of geometrically complex 3d range scans in a common frame of reference. The generated 3d representations, after automated registration, are useful for urban planning, historical preservation, or virtual reality applications. Man-made urban scenes provide an abundance of linear features that can be used for the solution of the problem. Many scenes though require the utilization of non-linear primitives. This paper provides a solution of the registration problem based on the robust detection and matching of circular features from the range data sets. We present results from experiments with complex range scans from the interior of a large-scale landmark urban structure (Grand Central Terminal, NYC), where traditional methods would fail. This work is part of a larger range registration system that is based on extracted features of multiple geometric types.

关键词： Image registration Layout Feature extraction Image edge detection Large-scale systems Shape Iterative closest point algorithm Computer science Robustness data mining

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