@article {13300,
	title = {Isodiamond Hierarchies: An Efficient Multiresolution Representation for Isosurfaces and Interval Volumes},
	journal = {Visualization and Computer Graphics, IEEE Transactions on},
	volume = {16},
	year = {2010},
	month = {2010///},
	pages = {583 - 598},
	abstract = {Efficient multiresolution representations for isosurfaces and interval volumes are becoming increasingly important as the gap between volume data sizes and processing speed continues to widen. Our multiresolution scalar field model is a hierarchy of tetrahedral clusters generated by longest edge bisection that we call a hierarchy of diamonds. We propose two multiresolution models for representing isosurfaces, or interval volumes, extracted from a hierarchy of diamonds which exploit its regular structure. These models are defined by subsets of diamonds in the hierarchy that we call isodiamonds, which are enhanced with geometric and topological information for encoding the relation between the isosurface, or interval volume, and the diamond itself. The first multiresolution model, called a relevant isodiamond hierarchy, encodes the isodiamonds intersected by the isosurface, or interval volume, as well as their nonintersected ancestors, while the second model, called a minimal isodiamond hierarchy, encodes only the intersected isodiamonds. Since both models operate directly on the extracted isosurface or interval volume, they require significantly less memory and support faster selective refinement queries than the original multiresolution scalar field, but do not support dynamic isovalue modifications. Moreover, since a minimal isodiamond hierarchy only encodes intersected isodiamonds, its extracted meshes require significantly less memory than those extracted from a relevant isodiamond hierarchy. We demonstrate the compactness of isodiamond hierarchies by comparing them to an indexed representation of the mesh at full resolution.},
	keywords = {Computer-Assisted;Imaging, data processing speed;edge bisection;encoding;interval volumes;isodiamond hierarchies;isosurfaces;mesh representation;minimal isodiamond hierarchy;multiresolution representation;multiresolution scalar field model;relevant isodiamond hierarchy;volume data, Theoretical;User-Computer Interface;, Three-Dimensional;Models},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2010.29},
	author = {Weiss,K. and De Floriani, Leila}
}
@article {12520,
	title = {Robust Estimation of Albedo for Illumination-Invariant Matching and Shape Recovery},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {31},
	year = {2009},
	month = {2009/05//},
	pages = {884 - 899},
	abstract = {We present a nonstationary stochastic filtering framework for the task of albedo estimation from a single image. There are several approaches in the literature for albedo estimation, but few include the errors in estimates of surface normals and light source direction to improve the albedo estimate. The proposed approach effectively utilizes the error statistics of surface normals and illumination direction for robust estimation of albedo, for images illuminated by single and multiple light sources. The albedo estimate obtained is subsequently used to generate albedo-free normalized images for recovering the shape of an object. Traditional shape-from-shading (SFS) approaches often assume constant/piecewise constant albedo and known light source direction to recover the underlying shape. Using the estimated albedo, the general problem of estimating the shape of an object with varying albedo map and unknown illumination source is reduced to one that can be handled by traditional SFS approaches. Experimental results are provided to show the effectiveness of the approach and its application to illumination-invariant matching and shape recovery. The estimated albedo maps are compared with the ground truth. The maps are used as illumination-invariant signatures for the task of face recognition across illumination variations. The recognition results obtained compare well with the current state-of-the-art approaches. Impressive shape recovery results are obtained using images downloaded from the Web with little control over imaging conditions. The recovered shapes are also used to synthesize novel views under novel illumination conditions.},
	keywords = {albedo estimation;error statistics;face recognition;illumination-invariant matching;nonstationary stochastic filtering;robust estimation;shape recovery;shape-from-shading approach;error statistics;face recognition;filtering theory;image matching;Algorithm, Automated;Photometry;Reproducibility of Results;Sensitivity and Specificity;, Computer-Assisted;Imaging, Three-Dimensional;Lighting;Pattern Recognition},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2008.135},
	author = {Biswas,S. and Aggarwal,G. and Chellapa, Rama}
}
@article {13125,
	title = {Constraint Integration for Efficient Multiview Pose Estimation with Self-Occlusions},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {30},
	year = {2008},
	month = {2008/03//},
	pages = {493 - 506},
	abstract = {Automatic initialization and tracking of human pose is an important task in visual surveillance. We present a part-based approach that incorporates a variety of constraints in a unified framework. These constraints include the kinematic constraints between parts that are physically connected to each other, the occlusion of one part by another, and the high correlation between the appearance of certain parts, such as the arms. The location probability distribution of each part is determined by evaluating appropriate likelihood measures. The graphical (nontree) structure representing the interdependencies between parts is utilized to "connect" such part distributions via nonparametric belief propagation. Methods are also developed to perform this optimization efficiently in the large space of pose configurations.},
	keywords = {Automated;Posture;Reproducibility of Results;Sensitivity and Specificity;Video Recording;Whole Body Imaging;, automatic initialization;constraint integration;graphical structure;human pose tracking;kinematic constraint;likelihood measure;location probability distribution;multiview pose estimation;nonparametric belief propagation;optimization;pose configuration;se, Computer-Assisted;Imaging, Three-Dimensional;Pattern Recognition},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2007.1173},
	author = {Gupta,A. and Mittal,A. and Davis, Larry S.}
}
@article {14977,
	title = {Interactive High-Resolution Isosurface Ray Casting on Multicore Processors},
	journal = {Visualization and Computer Graphics, IEEE Transactions on},
	volume = {14},
	year = {2008},
	month = {2008/06//may},
	pages = {603 - 614},
	abstract = {We present a new method for the interactive rendering of isosurfaces using ray casting on multicore processors. This method consists of a combination of an object-order traversal that coarsely identifies possible candidate three-dimensional (3D) data blocks for each small set of contiguous pixels and an isosurface ray casting strategy tailored for the resulting limited-size lists of candidate 3D data blocks. Our implementation scheme results in a compact indexing structure and makes careful use of multithreading and memory management environments commonly present in multicore processors. Although static screen partitioning is widely used in the literature, our scheme starts with an image partitioning for the initial stage and then performs dynamic allocation of groups of ray casting tasks among the different threads to ensure almost equal loads among the different cores while maintaining spatial locality. We also pay a particular attention to the overhead incurred by moving the data across the different levels of the memory hierarchy. We test our system on a two-processor Clovertown platform, each consisting of a Quad-Core 1.86-GHz Intel Xeon Processor and present detailed experimental results for a number of widely different benchmarks. We show that our system is efficient and scalable and achieves high cache performance and excellent load balancing, resulting in an overall performance that is superior to any of the previous algorithms. In fact, we achieve interactive isosurface rendering on a screen with 1.0242 resolution for all the data sets tested up to the maximum size that can fit in the main memory of our platform.},
	keywords = {compact indexing structure;interactive high-resolution isosurface ray casting;interactive isosurface rendering;memory management;multicore processor;multithreading;object-order traversal;static screen partitioning;multi-threading;multiprocessing systems;r, Computer-Assisted;Imaging, Computer-Assisted;User-Computer Interface;, Three-Dimensional;Information Storage and Retrieval;Reproducibility of Results;Sensitivity and Specificity;Signal Processing},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2007.70630},
	author = {Wang,Qin and JaJa, Joseph F.}
}
@article {12544,
	title = {Model Driven Segmentation of Articulating Humans in Laplacian Eigenspace},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {30},
	year = {2008},
	month = {2008/10//},
	pages = {1771 - 1785},
	abstract = {We propose a general approach using Laplacian Eigenmaps and a graphical model of the human body to segment 3D voxel data of humans into different articulated chains. In the bottom-up stage, the voxels are transformed into a high-dimensional (6D or less) Laplacian Eigenspace (LE) of the voxel neighborhood graph. We show that LE is effective at mapping voxels on long articulated chains to nodes on smooth 1D curves that can be easily discriminated, and prove these properties using representative graphs. We fit 1D splines to voxels belonging to different articulated chains such as the limbs, head and trunk, and determine the boundary between splines using the spline fitting error. A top-down probabilistic approach is then used to register the segmented chains, utilizing their mutual connectivity and individual properties. Our approach enables us to deal with complex poses such as those where the limbs form loops. We use the segmentation results to automatically estimate the human body models. While we use human subjects in our experiments, the method is fairly general and can be applied to voxel-based segmentation of any articulated object composed of long chains. We present results on real and synthetic data that illustrate the usefulness of this approach.},
	keywords = {3D voxel data segmentation, algorithms, Anatomic;Pattern Recognition, Artificial intelligence, Automated;Reproducibility of Results;Sensitivity and Specificity;Whole Body Imaging;, Computer simulation, Computer-Assisted;Imaging, curve fitting, Eigenvalues and eigenfunctions, graph theory, human articulation, human body graphical model, human motion analysis, HUMANS, Image Enhancement, Image Interpretation, Image motion analysis, image registration, Image segmentation, Laplace transforms, Laplacian eigenspace transform, model driven segmentation, probability, representative graph, skeleton registration, Smoothing methods, solid modelling, spline fitting error, splines (mathematics), Three-Dimensional;Joints;Models, top-down probabilistic approach, voxel neighborhood graph},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2007.70823},
	author = {Sundaresan, A. and Chellapa, Rama}
}
@article {12559,
	title = {Shape-and-Behavior Encoded Tracking of Bee Dances},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {30},
	year = {2008},
	month = {2008/03//},
	pages = {463 - 476},
	abstract = {Behavior analysis of social insects has garnered impetus in recent years and has led to some advances in fields like control systems and flight navigation. Manual labeling of insect motions required for analyzing the behaviors of insects requires significant investment of time and effort. In this paper, we propose certain general principles that help in simultaneous automatic tracking and behavior analysis, with applications in tracking bees and recognizing specific behaviors that they exhibit. The state space for tracking is defined using the position, orientation, and current behavior of the insect being tracked. The position and the orientation are parameterized using a shape model, whereas the behavior is explicitly modeled using a three-tier hierarchical motion model. The first tier (dynamics) models the local motions exhibited, and the models built in this tier act as a vocabulary for behavior modeling. The second tier is a Markov motion model built on top of the local motion vocabulary, which serves as the behavior model. The third tier of the hierarchy models the switching between behaviors, and this is also modeled as a Markov model. We address issues in learning the three-tier behavioral model, in discriminating between models, and in detecting and modeling abnormal behaviors. Another important aspect of this work is that it leads to joint tracking and behavior analysis instead of the traditional "track-and-then-recognize" approach. We apply these principles for tracking bees in a hive while they are executing the waggle dance and the round dance.},
	keywords = {Automated;Reproducibility of Results;Sensitivity and Specificity;Social Behavior;, Computer-Assisted;Imaging, Markov model;bee dance;behavior analysis;shape model;social insect;three-tier hierarchical motion model;tracking;video sequence;waggle dance;Markov processes;image sequences;optical tracking;video signal processing;zoology;Algorithms;Animal Communication;, Three-Dimensional;Information Storage and Retrieval;Male;Pattern Recognition},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2007.70707},
	author = {Veeraraghavan,A. and Chellapa, Rama and Srinivasan, M.}
}
@article {14892,
	title = {Shape Classification Using the Inner-Distance},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {29},
	year = {2007},
	month = {2007/02//},
	pages = {286 - 299},
	abstract = {Part structure and articulation are of fundamental importance in computer and human vision. We propose using the inner-distance to build shape descriptors that are robust to articulation and capture part structure. The inner-distance is defined as the length of the shortest path between landmark points within the shape silhouette. We show that it is articulation insensitive and more effective at capturing part structures than the Euclidean distance. This suggests that the inner-distance can be used as a replacement for the Euclidean distance to build more accurate descriptors for complex shapes, especially for those with articulated parts. In addition, texture information along the shortest path can be used to further improve shape classification. With this idea, we propose three approaches to using the inner-distance. The first method combines the inner-distance and multidimensional scaling (MDS) to build articulation invariant signatures for articulated shapes. The second method uses the inner-distance to build a new shape descriptor based on shape contexts. The third one extends the second one by considering the texture information along shortest paths. The proposed approaches have been tested on a variety of shape databases, including an articulated shape data set, MPEG7 CE-Shape-1, Kimia silhouettes, the ETH-80 data set, two leaf data sets, and a human motion silhouette data set. In all the experiments, our methods demonstrate effective performance compared with other algorithms},
	keywords = {Automated;Reproducibility of Results;Sensitivity and Specificity;, Computer-Assisted;Imaging, Euclidean distance;articulation invariant signatures;computer vision;inner distance;multidimensional scaling;part structure;shape classification;shape descriptors;shape silhouette;shortest path;computational geometry;computer vision;graph theory;image cla, Three-Dimensional;Pattern Recognition},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2007.41},
	author = {Ling,Haibin and Jacobs, David W.}
}
@article {14893,
	title = {Surface Dependent Representations for Illumination Insensitive Image Comparison},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {29},
	year = {2007},
	month = {2007/01//},
	pages = {98 - 111},
	abstract = {We consider the problem of matching images to tell whether they come from the same scene viewed under different lighting conditions. We show that the surface characteristics determine the type of image comparison method that should be used. Previous work has shown the effectiveness of comparing the image gradient direction for surfaces with material properties that change rapidly in one direction. We show analytically that two other widely used methods, normalized correlation of small windows and comparison of multiscale oriented filters, essentially compute the same thing. Then, we show that for surfaces whose properties change more slowly, comparison of the output of whitening filters is most effective. This suggests that a combination of these strategies should be employed to compare general objects. We discuss indications that Gabor jets use such a mixed strategy effectively, and we propose a new mixed strategy. We validate our results on synthetic and real images},
	keywords = {Automated;Reproducibility of Results;Sensitivity and Specificity;Subtraction Technique;, Computer-Assisted;Imaging, Gabor jets;Gaussian random surface;filter whitening;illumination;image comparison;image matching;lighting condition;multiscale oriented filter;surface dependent representation;image matching;image representation;Algorithms;Artificial Intelligence;Image En, Three-Dimensional;Information Storage and Retrieval;Lighting;Pattern Recognition},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2007.250602},
	author = {Osadchy,M. and Jacobs, David W. and Lindenbaum,M.}
}
@article {17968,
	title = {Geometry-dependent lighting},
	journal = {Visualization and Computer Graphics, IEEE Transactions on},
	volume = {12},
	year = {2006},
	month = {2006/04//march},
	pages = {197 - 207},
	abstract = {In this paper, we introduce geometry-dependent lighting that allows lighting parameters to be defined independently and possibly discrepantly over an object or scene based on the local geometry. We present and discuss light collages, a lighting design system with geometry-dependent lights for effective feature-enhanced visualization. Our algorithm segments the objects into local surface patches and places lights that are locally consistent but globally discrepant to enhance the perception of shape. We use spherical harmonics for efficiently storing and computing light placement and assignment. We also outline a method to find the minimal number of light sources sufficient to illuminate an object well with our globally discrepant lighting approach.},
	keywords = {Computer-Assisted;Imaging, feature-enhanced visualization;geometry-dependent light;light collage;light placement;lighting design system;computational geometry;data visualisation;lighting;Algorithms;Computer Graphics;Image Enhancement;Image Interpretation, Three-Dimensional;Information Storage and Retrieval;Lighting;User-Computer Interface;},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2006.30},
	author = {Lee,C. H and Hao,X. and Varshney, Amitabh}
}
@article {14979,
	title = {Isosurface Extraction and Spatial Filtering using Persistent Octree (POT)},
	journal = {Visualization and Computer Graphics, IEEE Transactions on},
	volume = {12},
	year = {2006},
	month = {2006/10//sept},
	pages = {1283 - 1290},
	abstract = {We propose a novel persistent octree (POT) indexing structure for accelerating isosurface extraction and spatial filtering from volumetric data. This data structure efficiently handles a wide range of visualization problems such as the generation of view-dependent isosurfaces, ray tracing, and isocontour slicing for high dimensional data. POT can be viewed as a hybrid data structure between the interval tree and the branch-on-need octree (BONO) in the sense that it achieves the asymptotic bound of the interval tree for identifying the active cells corresponding to an isosurface and is more efficient than BONO for handling spatial queries. We encode a compact octree for each isovalue. Each such octree contains only the corresponding active cells, in such a way that the combined structure has linear space. The inherent hierarchical structure associated with the active cells enables very fast filtering of the active cells based on spatial constraints. We demonstrate the effectiveness of our approach by performing view-dependent isosurfacing on a wide variety of volumetric data sets and 4D isocontour slicing on the time-varying Richtmyer-Meshkov instability dataset},
	keywords = {4D isocontour slicing;Richtmyer-Meshkov instability dataset;branch-on-need octree;hybrid data structure;isosurface extraction;persistent octree;spatial filtering;data visualisation;database indexing;feature extraction;octrees;spatial data structures;Algor, Computer-Assisted;Imaging, Three-Dimensional;Information Storage and Retrieval;User-Computer Interface;},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2006.157},
	author = {Shi,Q. and JaJa, Joseph F.}
}
@article {12618,
	title = {Robust ego-motion estimation and 3-D model refinement using surface parallax},
	journal = {Image Processing, IEEE Transactions on},
	volume = {15},
	year = {2006},
	month = {2006/05//},
	pages = {1215 - 1225},
	abstract = {We present an iterative algorithm for robustly estimating the ego-motion and refining and updating a coarse depth map using parametric surface parallax models and brightness derivatives extracted from an image pair. Given a coarse depth map acquired by a range-finder or extracted from a digital elevation map (DEM), ego-motion is estimated by combining a global ego-motion constraint and a local brightness constancy constraint. Using the estimated camera motion and the available depth estimate, motion of the three-dimensional (3-D) points is compensated. We utilize the fact that the resulting surface parallax field is an epipolar field, and knowing its direction from the previous motion estimates, estimate its magnitude and use it to refine the depth map estimate. The parallax magnitude is estimated using a constant parallax model (CPM) which assumes a smooth parallax field and a depth based parallax model (DBPM), which models the parallax magnitude using the given depth map. We obtain confidence measures for determining the accuracy of the estimated depth values which are used to remove regions with potentially incorrect depth estimates for robustly estimating ego-motion in subsequent iterations. Experimental results using both synthetic and real data (both indoor and outdoor sequences) illustrate the effectiveness of the proposed algorithm.},
	keywords = {3D model refinement, algorithms, Artificial intelligence, Automated;Subtraction Technique;, Computer-Assisted;Imaging, constant parallax model, depth based parallax model, digital elevation map, epipolar field, Image Enhancement, Image Interpretation, iterative algorithm, iterative methods, Motion estimation, robust ego-motion estimation, smooth parallax field, surface parallax, Three-Dimensional;Information Storage and Retrieval;Pattern Recognition},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2005.864167},
	author = {Agrawal,A. and Chellapa, Rama}
}
@article {17966,
	title = {Saliency-guided Enhancement for Volume Visualization},
	journal = {Visualization and Computer Graphics, IEEE Transactions on},
	volume = {12},
	year = {2006},
	month = {2006/10//sept},
	pages = {925 - 932},
	abstract = {Recent research in visual saliency has established a computational measure of perceptual importance. In this paper we present a visual-saliency-based operator to enhance selected regions of a volume. We show how we use such an operator on a user-specified saliency field to compute an emphasis field. We further discuss how the emphasis field can be integrated into the visualization pipeline through its modifications of regional luminance and chrominance. Finally, we validate our work using an eye-tracking-based user study and show that our new saliency enhancement operator is more effective at eliciting viewer attention than the traditional Gaussian enhancement operator},
	keywords = {Computer-Assisted;Imaging, Ocular;Humans;Image Enhancement;Image Interpretation, saliency-guided enhancement;visual-saliency-based operator;volume rendering;volume visualization;data visualisation;rendering (computer graphics);Algorithms;Attention;Computer Graphics;Eye Movements;Fixation, Three-Dimensional;User-Computer Interface;},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2006.174},
	author = {Kim,Y. and Varshney, Amitabh}
}
@article {12661,
	title = {Bayesian algorithms for simultaneous structure from motion estimation of multiple independently moving objects},
	journal = {Image Processing, IEEE Transactions on},
	volume = {14},
	year = {2005},
	month = {2005/01//},
	pages = {94 - 109},
	abstract = {The problem of simultaneous structure from motion estimation for multiple independently moving objects from a monocular image sequence is addressed. Two Bayesian algorithms are presented for solving this problem using the sequential importance sampling (SIS) technique. The empirical posterior distribution of object motion and feature separation parameters is approximated by weighted samples. The first algorithm addresses the problem when only two moving objects are present. A singular value decomposition (SVD)-based sample clustering algorithm is shown to be capable of separating samples related to different objects. A pair of SIS procedures is used to track the posterior distribution of the motion parameters. In the second algorithm, a balancing step is added into the SIS procedure to preserve samples of low weights so that all objects have enough samples to propagate empirical motion distributions. By using the proposed algorithms, the relative motions of all the moving objects with respect to the camera can be simultaneously estimated. Both algorithms have been tested on synthetic and real- image sequences. Improved results have been achieved.},
	keywords = {Automated;Reproducibility of Results;Sensitivity and Specificity;Signal Processing, Bayesian algorithm;clustering algorithm;empirical posterior distribution;feature separation parameter;monocular image sequence;motion estimation;multiple independently moving object;object motion;real-image sequence;sequential importance sampling techniqu, Biological;Models, Computer-Assisted;Imaging, Computer-Assisted;Pattern Recognition, Computer-Assisted;Subtraction Technique;Video Recording;Walking;, Statistical;Movement;Numerical Analysis, Three-Dimensional;Information Storage and Retrieval;Models},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2004.837551},
	author = {Qian,Gang and Chellapa, Rama and Qinfen Zheng}
}
@article {12645,
	title = {Matching shape sequences in video with applications in human movement analysis},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {27},
	year = {2005},
	month = {2005/12//},
	pages = {1896 - 1909},
	abstract = {We present an approach for comparing two sequences of deforming shapes using both parametric models and nonparametric methods. In our approach, Kendall{\textquoteright}s definition of shape is used for feature extraction. Since the shape feature rests on a non-Euclidean manifold, we propose parametric models like the autoregressive model and autoregressive moving average model on the tangent space and demonstrate the ability of these models to capture the nature of shape deformations using experiments on gait-based human recognition. The nonparametric model is based on dynamic time-warping. We suggest a modification of the dynamic time-warping algorithm to include the nature of the non-Euclidean space in which the shape deformations take place. We also show the efficacy of this algorithm by its application to gait-based human recognition. We exploit the shape deformations of a person{\textquoteright}s silhouette as a discriminating feature and provide recognition results using the nonparametric model. Our analysis leads to some interesting observations on the role of shape and kinematics in automated gait-based person authentication.},
	keywords = {Automated;Photography;Reproducibility of Results;Sensitivity and Specificity;Subtraction Technique;Video Recording;, autoregressive moving average model;deforming shapes;dynamic time-warping;feature extraction;gait-based human recognition;human movement analysis;matching shape sequences;video;autoregressive moving average processes;feature extraction;image matching;imag, Biological;Models, Computer-Assisted;Imaging, Statistical;Movement;Pattern Recognition, Three-Dimensional;Leg;Models},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2005.246},
	author = {A,Veeraraghavan and Roy-Chowdhury, A.K. and Chellapa, Rama}
}
@article {12654,
	title = {Statistical bias in 3-D reconstruction from a monocular video},
	journal = {Image Processing, IEEE Transactions on},
	volume = {14},
	year = {2005},
	month = {2005/08//},
	pages = {1057 - 1062},
	abstract = {The present state-of-the-art in computing the error statistics in three-dimensional (3-D) reconstruction from video concentrates on estimating the error covariance. A different source of error which has not received much attention is the fact that the reconstruction estimates are often significantly statistically biased. In this paper, we derive a precise expression for the bias in the depth estimate, based on the continuous (differentiable) version of structure from motion (SfM). Many SfM algorithms, or certain portions of them, can be posed in a linear least-squares (LS) framework Ax=b. Examples include initialization procedures for bundle adjustment or algorithms that alternately estimate depth and camera motion. It is a well-known fact that the LS estimate is biased if the system matrix A is noisy. In SfM, the matrix A contains point correspondences, which are always difficult to obtain precisely; thus, it is expected that the structure and motion estimates in such a formulation of the problem would be biased. Existing results on the minimum achievable variance of the SfM estimator are extended by deriving a generalized Cramer-Rao lower bound. A detailed analysis of the effect of various camera motion parameters on the bias is presented. We conclude by presenting the effect of bias compensation on reconstructing 3-D face models from rendered images.},
	keywords = {3D face models, 3D video reconstruction, algorithms, artifacts, Artificial intelligence, Automated;Signal Processing, bias compensation, bundle adjustment, camera motion estimation, Computer simulation, Computer-Assisted;Imaging, Computer-Assisted;Subtraction Technique;Video Recording;, depth estimate, error covariance estimation, error statistics, generalized Cramer-Rao lower bound, Image Enhancement, Image Interpretation, Image reconstruction, initialization procedures, least squares approximations, linear least-squares framework, monocular video, motion compensation, Motion estimation, statistical bias, Statistical;Pattern Recognition, structure from motion algorithms, Three-Dimensional;Information Storage and Retrieval;Models, video signal processing},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2005.849775},
	author = {Roy-Chowdhury, A.K. and Chellapa, Rama}
}
@article {12698,
	title = {An information theoretic criterion for evaluating the quality of 3-D reconstructions from video},
	journal = {Image Processing, IEEE Transactions on},
	volume = {13},
	year = {2004},
	month = {2004/07//},
	pages = {960 - 973},
	abstract = {Even though numerous algorithms exist for estimating the three-dimensional (3-D) structure of a scene from its video, the solutions obtained are often of unacceptable quality. To overcome some of the deficiencies, many application systems rely on processing more data than necessary, thus raising the question: how is the accuracy of the solution related to the amount of data processed by the algorithm? Can we automatically recognize situations where the quality of the data is so bad that even a large number of additional observations will not yield the desired solution? Previous efforts to answer this question have used statistical measures like second order moments. They are useful if the estimate of the structure is unbiased and the higher order statistical effects are negligible, which is often not the case. This paper introduces an alternative information-theoretic criterion for evaluating the quality of a 3-D reconstruction. The accuracy of the reconstruction is judged by considering the change in mutual information (MI) (termed as the incremental MI) between a scene and its reconstructions. An example of 3-D reconstruction from a video sequence using optical flow equations and known noise distribution is considered and it is shown how the MI can be computed from first principles. We present simulations on both synthetic and real data to demonstrate the effectiveness of the proposed criterion.},
	keywords = {3D reconstruction, algorithms, Artificial intelligence, Automated;Reproducibility of Results;Sensitivity and Specificity;Signal Processing, Computer Graphics, Computer-Assisted;Imaging, Computer-Assisted;Software Validation;Subtraction Technique;Video Recording;, Image Enhancement, Image Interpretation, Image reconstruction, Image sequences, information theoretic criterion, Mutual information, NOISE, noise distribution, optical flow equations, second order moments, statistical analysis, Three-Dimensional;Information Storage and Retrieval;Information Theory;Movement;Pattern Recognition, Video sequences, video signal processing},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2004.827240},
	author = {Roy-Chowdhury, A.K. and Chellapa, Rama}
}
@article {13325,
	title = {Selective refinement queries for volume visualization of unstructured tetrahedral meshes},
	journal = {Visualization and Computer Graphics, IEEE Transactions on},
	volume = {10},
	year = {2004},
	month = {2004///},
	pages = {29 - 45},
	abstract = {We address the problem of the efficient visualization of large irregular volume data sets by exploiting a multiresolution model based on tetrahedral meshes. Multiresolution models, also called Level-Of-Detail (LOD) models, allow encoding the whole data set at a virtually continuous range of different resolutions. We have identified a set of queries for extracting meshes at variable resolution from a multiresolution model, based on field values, domain location, or opacity of the transfer function. Such queries allow trading off between resolution and speed in visualization. We define a new compact data structure for encoding a multiresolution tetrahedral mesh built through edge collapses to support selective refinement efficiently and show that such a structure has a storage cost from 3 to 5.5 times lower than standard data structures used for tetrahedral meshes. The data structures and variable resolution queries have been implemented together with state-of-the art visualization techniques in a system for the interactive visualization of three-dimensional scalar fields defined on tetrahedral meshes. Experimental results show that selective refinement queries can support interactive visualization of large data sets.},
	keywords = {Automated;Signal Processing, Computer-Assisted;Imaging, Computer-Assisted;User-Computer Interface;, data structure;geometric modeling;interactive visualization;large data sets;multiresolution model;selective refinement queries;unstructured tetrahedral meshes;variable resolution queries;volume data visualization;data visualisation;mesh generation;query p, Three-Dimensional;Online Systems;Pattern Recognition},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2004.1260756},
	author = {Cignoni,P. and De Floriani, Leila and Magillo,P. and Puppo,E. and Scopigno,R.}
}
