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A flexible projector-camera system for multi-planar displays

A flexible projector-camera system for multi-planar displays

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Proceedings of the 2004 ieee computer society conference on computer vision and pattern recognition, cvpr 2004

作者： Ashdown, Mark Flagg, Matthew Sukthankar, Rahul Rehg, James M. University of Cambridge Computer Lab. J.J. Thomson Avenue Cambridge CB3 0FD United Kingdom College of Computing Georgia Institute of Technology Atlanta GA United States Intel Research Pittsburgh 416 S. Craig St. Pittsburgh PA United States Robotics Institute Carnegie Mellon University Pittsburgh PA United States

We present a novel multi-planar display system based on an uncalibrated projector-camera pair. Our system exploits the juxtaposition of planar surfaces in a room to create ad-hoc visualization and display capabilities. In an office setting, for example, a desk pushed against a wall provides two perpendicular surfaces that can simultaneously display elevation and plan views of an architectural model. In contrast to previous room-level projector-camera systems, our method is based on a flexible calibration procedure that requires a minimum amount of information for the geometry of the multi-planar surface scenario. A number of display configurations can be created on any available planar surfaces using a single commodity projector and camera. The key to our calibration approach is an efficient technique for simultaneously localizing multiple planes and a robust planar metric rectification method which can tolerate a restricted camera field-of-view and requires no special calibration objects. We demonstrate the robustness of our calibration method using real and synthetic images and present several applications of our display system.

关键词： Projection systems

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Mosaicing with parallax using time warping

Mosaicing with parallax using time warping

引用

2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Rav-Acha, Alex Shor, Yael Peleg, Shmuel School of Computer Science and Engineering Hebrew University of Jerusalem Jerusalem91904 Israel Humaneyes Technologies Ltd. Israel

2D image alignment methods are applied successfully for mosaicing aerial images, but fail when the camera moves in a 3D scene. Such methods can not handle 3D parallax, resulting in distorted mosaicing. General egomotion methods are slow, and do not have the robustness of 2D alignment methods. We propose to use the x-y-t space-time volume as a tool for depth invariant mosaicing. When the camera moves on a straight line in the x direction, a y-t slice of the space-time volume is a panoramic mosaic, while a x-t slice is an EPI plane. Time warping, which is a resampling of the t axix, is used to form straight feature lines in the EPI planes. This process will simultaneously give best panoramic mosaic in the y-t slices. This approach is as robust as 2D alignment methods, while giving depth invariant motion ("ego motion"). Extensions for two dimensional camera motion on a plane are also described, with applications for 2D mosaicing, and for image based rendering such as "light field". © 2004 ieee.

关键词： Cameras

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Outlier rejection in deformable model tracking

Outlier rejection in deformable model tracking

引用

2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Goldenstein, Siome Vogler, Christian Stolfi, Jorge Pavlovic, Vladimir Metaxas, Dimitris Instituto de Computação - Unicamp Caixa Postal 6176 Campinas SP13084-971 Brazil Gallaudet Research Institute Gallaudet University 800 Florida Ave. NE WashingtonDC20002-3695 United States Department of Computer Science Rutgers University 110 Frelinghuysen Road PiscatawayNJ08854-8019 United States

Deformable model tracking is a powerful methodology that allows us to track the evolution of high-dimensional parameter vectors from uncalibrated monocular video sequences. The core of the approach consists of using low-level vision algorithms, such as edge trackers or optical flow, to collect a large number of 2D displacements, or motion measurements, at selected model points and mapping them into 3D space with the model Jacobians. However, the low-level algorithms are prone to errors and outliers, which can skew the entire tracking procedure if left unchecked. There are several known techniques in the literature, such as RANSAC, that can find and reject outliers. Unfortunately, these approaches are not easily mapped into the deformable model tracking framework, where there is no closed-form algebraic mapping from samples to the underlying parameter space. In this paper we present two simple, yet effective ways to find the outliers. We validate and compare these approaches in an 11-parameter deformable face tracking application against ground truth data. © 2004 ieee.

关键词： Mapping

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Optimal subclass discovery for discriminant analysis

Optimal subclass discovery for discriminant analysis

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Zhu, Manli Martínez, Aleix M. Depart. of Electrical and Computer Engineering Ohio State University United States

Discriminant Analysis (DA) has had a big influence in many scientific disciplines. Unfortunately, DA algorithms need to make assumptions on the type of data available and, therefore, are not applicable everywhere. For example, when the data of each class can be represented by a single Gaussian and these share a common covariance matrix, Linear Discriminant Analysis (LDA) is a good option. In other cases, other DA approaches may be preferred. And, unfortunately, there still exist applications where no DA algorithm will correctly represent reality and, therefore, unsupervised techniques, such as Principal Components Analysis (PCA), may perform better. This paper first presents a theoretical study to define when and (most importantly) why DA techniques fail (Section 2). This is then used to create a new DA algorithm that can adapt to the training data available (Sections 2 and 3). The first main component of our solution is to design a method to automatically discover the optimal set of subclasses in each class. We will show that when this is achieved, optimal results can be obtained. The second main component of our algorithm is given by our theoretical study which defines a way to rapidly select the optimal number of subclasses. We present experimental results on two applications (object categorization and face recognition) and show that our method is always comparable or superior to LDA, Direct LDA (DLDA), Nonparametric DA (NDA) and PCA. © 2004 ieee.

关键词： Discriminant analysis

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Semantic-level understanding of human actions and interactions using event hierarchy

Semantic-level understanding of human actions and interactio...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Park, Sangho Aggarwal, J.K. Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States

Understanding human behavior in video data is essential in numerous applications including surveillance, video annotation/retrieval, and human-computer interfaces. This paper describes a framework for recognizing human actions and interactions in video by using three levels of abstraction. At low level, the poses of individual body parts including head, torso, arms and legs are recognized using individual Bayesian networks (BNs), which are then integrated to obtain an overall body pose. At mid level, the actions of a single person are modeled using a dynamic Bayesian network (DBN) with temporal links between identical states of the Bayesian network at time t and t+1. At high level, the results of mid-level descriptions for each person are juxtaposed along a common time line to identify an interaction between two persons. The linguistic 'verb argument structure' is used to represent human action in terms of triplets. Spatial and temporal constraints are used for a decision tree to recognize specific interactions. A meaningful semantic description in terms of subject-verb-object is obtained. Our method provides a user-friendly natural-language description of several human interactions, and correctly describes positive, neutral, and negative interactions occurring between two persons. Example sequences of real persons are presented to illustrate the paradigm. © 2004 ieee.

关键词： Bayesian networks

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Non-rigid motion estimation using the robust tensor method

Non-rigid motion estimation using the robust tensor method

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Palaniappan, K. Jiang, Hai S. Baskin, Tobias I. Multimedia Communications and Visualization Laboratory Department of Computer Science University of Missouri-Columbia ColumbiaMO65211 United States Biology Department University of Massachusetts 611 N. Pleasant St. AmherstMA01003 United States

This paper presents a new technique that couples tensor based image flow with robust statistical estimation models to produce dense accurate velocity fields. The 3D orientation structure tensor of the spatiotemporal varying light intensity field is used to estimate local non-rigid image motions. Previous work has shown that in highly uniform regions that lack salient corner and edge information or with noisy measurements the structure tensor approach can lead to spurious velocity estimates. The proposed algorithm improves estimates of the deformable image flow in these regions by minimizing a robust tensor functional that includes regularization and penalty terms. The robust tensor functional explicitly incorporates a temporal photometric consistency term. The combined robust tensor method is formulated as a global constrained optimization over the 3D spatiotemporal light intensity volume and recovers scientifically accurate velocity fields. An attractive aspect of the robust tensor method is simultaneous segmentation and velocity estimation. Experimental results using image sequences of biological motion captured using a calibrated video microscope reveals new biophysical insights at subcellular micron scale resolutions. © 2004 ieee.

关键词： Tensors

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A particle filter without dynamics for robust 3D face tracking

A particle filter without dynamics for robust 3D face tracki...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Lu, Le Dai, Xiang-Tian Hager, Gregory Computational Interaction and Robotics Lab Computer Science Department Johns Hopkins University BaltimoreMD21218 United States

Particle filtering is a very popular technique for sequential state estimation problem. However its convergence greatly depends on the balance between the number of particles/hypotheses and the fitness of the dynamic model. In particular, in cases where the dynamics are complex or poorly modeled, thousands of particles are usually required for real applications. This paper presents a hybrid sampling solution that combines the sampling in the image feature space and in the state space via RANSAC and particle filtering, respectively. We show that the number of particles can be reduced to dozens for a full 3D tracking problem which contains considerable noise of different types. For unexpected motions, a specific set of dynamics may not exist, but it is avoided in our algorithm. The theoretical convergence proof [1, 3] for particle filtering when integrating RANSAC is difficult, but we address this problem by analyzing the likelihood distribution of particles from a real tracking example. The sampling efficiency (on the more likely areas) is much higher by the use of RANSAC. We also discuss the tracking quality measurement in the sense of entropy or statistical testing. The algorithm has been applied to the problem of 3D face pose tracking with changing moderate or intense expressions. We demonstrate the validity of our approach with several video sequences acquired in an unstructured environment. © 2004 ieee.

关键词： Dynamics

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Boundary matting for view synthesis

Boundary matting for view synthesis

引用

2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Hasinoff, Samuel W. Kang, Sing Bing Szeliski, Richard Dept. of Computer Science University of Toronto TorontoM5S 3G4 Canada Interactive Visual Media Group Microsoft Research RedmondWA98052 United States

In the last few years, new view synthesis has emerged as an important application of 3D stereo reconstruction. While the quality of stereo has improved, it is still imperfect, and a unique depth is typically assigned to every pixel. This is problematic at object boundaries, where the pixel colors are mixtures of foreground and background colors. Interpolating views without explicitly accounting for this effect results in objects with a "cut-out" appearance. To produce seamless view interpolation, we propose a method called boundary matting, which represents each occlusion boundary as a 3D curve. We show how this method exploits multiple views to perform fully automatic alpha matting and to simultaneously refine stereo depths at the boundaries. The key to our approach is the unifying 3D representation of occlusion boundaries estimated to sub-pixel accuracy. Starting from an initial estimate derived from stereo, we optimize the curve parameters and the foreground colors near the boundaries. Our objective function maximizes consistency with the input images, favors boundaries aligned with strong edges, and damps large perturbations of the curves. Experimental results suggest that this method enables high-quality view synthesis with reduced matting artifacts. © 2004 ieee.

关键词： Color

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Spline-based motion recovery for 3D surfaces using nonrigid shape properties

Spline-based motion recovery for 3D surfaces using nonrigid ...

引用

2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Li, Min Kambhamettu, Chandra Stone, Maureen Department of Computer and Information Sciences University of Delaware NewarkDE19716 United States Vocal Tract Visualization Lab University of Maryland Dental School BaltimoreMD21201 United States

We present a spline-based nonrigid motion and point correspondence recovery method for 3D surfaces. This method is based on differential geometry. Shape information is used to recover the point correspondences. In contrast to the majority of shape-based methods which assume that shape (unit normal, curvature) changes are minimumafter motion, our method focuses on the nonrigid relationship between before-motion and after-motion shapes. This nonrigid shape relationship is described by modeling the underlying non-rigid motion;we model it as a spline transformation which has global control over the entire motion field along with the local deformation integrated within. This provides our method certain advantages over some pure differential geometric methods which also utilize the nonrigid shape relationship but only work on local areas without a global control. For example, motion regularity is hard to implement in these pure differential geometric methods but is not a problem when the motion field is controlled by a spline transformation. Furthermore, the small deformation constraint introduced by the previous works is relaxed in our method. Experiments on both synthetic and real motions have been conducted. The quantitive and qualitative evaluations of our method are presented in this paper. © 2004 ieee.

关键词： Recovery

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The dense estimation of motion and appearance in layers

The dense estimation of motion and appearance in layers

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Yalcin, Hulya Black, Michael J. Fablet, Ronan Division of Engineering Brown University ProvidenceRI02912 United States Computer Science Brown University ProvidenceRI02912 United States LASAA IFREMER Plouzane29280 France

Segmenting image sequences into meaningful layers is fundamental to many applications such as surveillance, tracking, and video summarization. Background subtraction techniques are popular for their simplicity and, while they provide a dense (pixelwise) estimate of foreground/background, they typically ignore image motion which can provide a rich source of information about scene structure. Conversely, layered motion estimation techniques typically ignore the temporal persistence of image appearance and provide parametric (rather than dense) estimates of optical flow. Recent work adaptively combines motion and appearance estimation in a mixture model framework to achieve robust tracking. Here we extend mixture model approaches to cope with dense motion and appearance estimation. We develop a unified Bayesian framework to simultaneously estimate the appearance of multiple image layers and their corresponding dense flow fields from image sequences. Both the motion and appearance models adapt over time and the probabilistic formulation can be used to provideasegmentation of thescene into foreground/background regions. This extension of mixture models includes prior probability models for the spatial and temporal coherence of motion and appearance. Experimental results show that the simultaneous estimation of appearance models and flow fields in multiple layers improves the estimation of optical flow at motion boundaries. © 2004 ieee.

关键词： Optical flows

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