Image based imposters suffer from common errors called disocclusion artifacts where portions of the scene that should be occluded by real geometry are visible when using image based imposters. These artifacts are the result of parallax error created by camera motion where regions of a mesh that were not visible at the time of imposter generation have become visible. This document presents an analysis of a computationally inexpensive on-line technique [Mourning et al. 2014] to resolve these disocclusions by stretching existing imposter [Maciel and Shirley 1995] texture information over new geometry bridging the gap between imposters. [Mourning et al. 2014] only presented automatic metrics showing improved image quality compared to traditional techniques; in order to corroborate the findings in [Mourning et al. 2014], human trials were performed to determine if human subjects found a similar increase in image quality. Results show a statistically significant improvement in image quality over traditional imposters.

This paper presents a technique for interactively colliding with and deforming mesostructures at a per-texel level. It is compatible with a broad range of existing mesostructure rendering techniques including both safe and unsafe ray-height field intersection algorithms. This technique is able to replace traditional 3D geometrical deformations (vertex-based) with 2D image space operations (pixel-based) that are parallelized on a GPU without CPU-GPU data shuffling and integrates well with existing physics engines. Additionally, surface and material properties may be specified at a per-texel level enabling a mesostructure to possess varying attributes intrinsic to its surface and collision behavior. Furthermore, this approach may replace traditional decals with image-based operations that naturally accumulate deformations without inserting any new geometry. This technique provides a simple and efficient way to make almost every surface in a virtual world responsive to user actions and events. It requires no preprocessing time and storage requirements of one additional texture or less. The algorithm uses existing inverse displacement map algorithms as well as existing physics engines and can be easily incorporated into new or existing game pipelines.

This paper presents a technique for interactively deforming and colliding with mesostructures at a per-texel level. It is compatible with a broad range of existing mesostructure rendering techniques including both safe and unsafe ray-height field intersection algorithms. This technique integrates well with existing physics engines and is able to reduce traditional 3D geometrical deformations (vertex-based) to 2D image space operations (pixel-based) that are parallelized on a GPU without CPU-GPU data shuffling. Additionally, surface and material properties may be specified at a per-texel level enabling a mesostructure to possess varying attributes intrinsic to its surface and collision behavior; furthermore, this offers an image-based alternative to traditional decals. This technique provides a simple way to make almost every surface in a virtual world responsive to user actions and events. It requires no preprocessing time and storage requirements of one additional texture or less. The algorithm uses existing displacement map algorithms as well as existing physics engines and can be easily incorporated into new or existing game pipelines.

This paper describes a visualization system for the Joint Precision Aircraft Landing System (JPALS) that integrates remote sensor data with well-known databases of terrain imagery, elevation, and surveyed aviation locations. This visualization system allows teams of research engineers and managers to collaborate in real-time, during test flights, in a distributed fashion. Each user interacts with their own copy of the virtual world, updated constantly in real-time, to manipulate and investigate in a fashion that best accomplishes their own specific task. This allows the entire team to collaborate simultaneously, which mitigates the common latency associated with team members performing offline tasks, such as inspecting log files or verifying MatLab plots. Test flights utilizing our visualization system have shown that it enabled the research team to make decisions on the fly, such as changing the antenna type and placement, and also allowed post-flight analysis and prediction of desirable changes. It could, for instance, predict optimal antenna placement for a given flight path. This can save a project the large expense of performing additional test flights if analysis had been performed offline between flights. Since our system is GPS based, it can be used as an alternate truth system to validate traditional instrument approach and landing systems. The recording and playback features of our visualization can also be used as a teaching aid in flight training for both pilots and air traffic controllers.

In this paper, we propose a distribution-based active contour model for brain MRI segmentation. As a generalization of the Chan-Vese piecewise-constant model, our solution uses Bayesian a posterior probabilities as the driving forces for curve evolution. Distribution prior, if available, can be seamlessly integrated into the level set evolution procedure. Unlike other region-based active contour models, our solution relaxes the global piecewise-constant assumption, and uses locally varying Gaussians to better account for intensity inhomogeneity and local variations existing in many MR images. More accurate and robust segmentations are therefore achieved. Experiments conducted on synthetic and real brain MRIs demonstrate the improvement made by our model. 1

Detecting and recognizing objects in unstructured environments is one of the most challenging tasks in computer vision research. We propose an innovative algorithm, called deformable illumination, to address the problem of illumination variance in natural environments. Parallel to the role of deformable shape in object recognition, deformable illumination is designed as an object detection technique. A unified framework presented here integrates both deformable illumination and deformable shape as a simultaneous scheme for object detection and recognition in unstructured environments. Experimental results show the effectiveness of deformable illumination in addressing illumination variance.

As one of the key techniques for futuristic man-machine interface, facial expression analysis has received much attention in recent years. This paper proposes a hierarchical approach to facial expression recognition in image sequences by exploiting both spatial and temporal characteristics within the framework of hierarchical hidden Markov models (HHMMs). Human faces are automatically detected in the maximum likelihood sense. Gabor-wavelet based features are extracted from image sequences to capture the subtle changes of facial expressions. Four prototype emotions; i.e. happiness, anger, fear and sadness, are investigated using the Cohn-Kanade database and an average of 90.98% person-independent recognition rate is achieved. We also demonstrate that HHMMs outperform HMMs for modeling image sequences with multilevel statistical structure.

Facial event mining is one of the key techniques for automatic human face analysis. It plays an important role in human computer interaction. This paper proposes a new approach to facial event recognition by combining active shape models (ASMs) and coupled hidden Markov models (CHMMs). Based on the assumption that a complex facial event can be decomposed into multiple coupled processes, ASMs are used to track global facial features and to decouple pattern attributes for upper and lower faces separately. These two interacting processes are modeled as a CHMM for training and recognition. Four basic facial events are investigated. Preliminary experiments yield consistent results that show the significant advantage of CHMMs over conventional HMMs for facial event mining in video.

The paper proposes an adaptive framework for shape-based image retrieval with relevance feedback. The motivation is to find an adjustable shape representation scheme that can account for feedback information. Relevance feedback is modeled as a dynamic eigenspace decomposition, and is used to classify the database into relevant and irrelevant groups with respect to the query. Eigenvectors of the subspace are updated by optimizing a linear transform with respect to the J3class separability criterion. Experimental results show that the proposed approach can effectively capture a user's perceptual subjectivity

Although significant research effort has been devoted to the natural scene analysis, there hasn't been much work on natural scene synthesis. The research of such nature can help to understand the hidden structure of natural texture and the illumination patterns for classification and segmentation purposes. The common texture synthesis methods are not suitable for natural scene synthesis due to inhomogeneity of the natural textures. In this paper, we propose a new natural scene synthesis framework based on multiple eigenspace decomposition, which is a natural extension of principle component analysis (PCA). Two levels of multiple eigenspaces are used; label level multiple eigenspaces for generating depth map and color level multiple eigenspaces for generating nature textures to fill the label maps. Experimental results are presented to show the effectiveness of the proposed framework.

Abstract—This paper describes a test-bed for technology that unifies agent based computing and adaptive resource management for dynamic real-time systems. We describe a unified framework that combines a hybrid agent based architecture with explicit resource adapting mechanisms. I.

In this paper, we propose the volume between two surfaces normalized by the surface area (interpreted as average distance between two surfaces) as an invariant quantitative measure for comparing surface reconstruction results of the explicit form, z(x,y). The invariant property of the volume quantity provides the same measure with respect to an arbitrary coordinate system. By normalizing the volume by the surface area, the values of the measure can be compared for different size of images. We also present a novel computationally simple and efficient way of computing the volume between two surfaces and the surface area using a least-squared-error plane approximation of a surface patch defined over a rectangular grid. Experiments indicate that the method gives equivalent performance as other more complicated and computationally expensive methods. The advantages of this new method are that computation is simple and efficient.

We describe a method to automatically find gradient thresholds to separate edge from nonedge pixels. A statistical model that is the weighted sum of two gamma densities corresponding to edge and nonedge pixels is used to identify a threshold. Results closely match human perceptual thresholds even under low signal-to-noise ratio (SNR) levels.

Recently, there has been a great increase in interest in using three dimensional stereoscopic displays to provide viewers with realistic 3D views of objects of interest. Some applications where stereoscopic displays are becoming popular include medical visualization, visualization of meteorological data, and various virtual reality applications. To quantify the effectiveness of stereoscopic systems over conventional monoscopic systems, well-designed experiments and data analysis methods are necessary. This task requires the combined effort of application scientists and experts in experimental design. Lack of interdisciplinary collaboration is a primary weakness of many stereoscopic display studies, resulting in the neglect of many important but subtle experimental issues. In this paper, we discuss specific issues that arise in the design of studies to determine the effectiveness of digital stereo imagery. Issues concerning statistical analysis of the experimental data are also discussed. References to related literature from engineering, computer graphics, and psychophysics are given. The issues developed herein provide a guideline for the design of studies to compare observer performance when using different imaging modalities.

This paper describes the application of a first order regularization technique to the reconstruction of visible surfaces. Our approach is a computationally efficient first order method that simultaneously achieves approximate invariance and preservation of discontinuities. It is also robust with respect to the smoothing parameter /spl lambda/. The robustness property to /spl lambda/ allows a free choice of /spl lambda/ without struggling to determine an optimal /spl lambda/ that provides the best reconstruction. A new approximately invariant first order stabilizing function for surface reconstruction is obtained by employing a first order Taylor expansion of a nonconvex invariant stabilizing function that is expanded at the estimated value of the squared gradient instead of at zero. The data compatibility measure is the squared perpendicular distance between the reconstructed surface and the constraint surface. This combination of stabilizing function and data compatibility measure is necessary to achieve invariance with respect to rotations and translations. Sharp preservation of discontinuities is achieved by a weighted sum of adjacent pixels. The results indicate that the proposed methods perform well on sparse noisy range data. In addition, the volume between two surfaces normalized by the surface area (interpreted as average distance between two surfaces) is proposed as an invariant measure for the comparison of reconstruction results.>

Reports the diagnostic performance of observers in detecting abnormalities in computer-generated mammogram-like images. A mathematical model of the human breast is defined in which breast tissues are simulated by spheres of different sizes and densities. Images are generated by casting rays from a specified source, through the model, and onto an image plane. Observer performance when using two viewing modalities (stereo versus mono) is compared. In the stereo viewing mode, images are presented to the observer (wearing liquid-crystal display glasses), such that the left eye sees the left image only and the right eye sees the right image only. In this way, the images can be fused by the observer to obtain a sense of depth. In the mono viewing mode, identical images are presented to the left and right eyes so that no binocular disparities will be produced by the images. Observer response data are evaluated using receiver operating characteristic (ROC) analysis to characterize any difference in detectability of abnormalities (in either the density or the arrangement of simulated tissue densities) using the two viewing modes. The authors' experimental results indicate the clear superiority of stereo viewing for detection of arrangement abnormalities. For detection of density abnormalities, the performance of the two viewing modes is similar. These preliminary results suggest that stereomammography may permit easier detection of certain tissue abnormalities, perhaps providing a route to earlier tumor detection in cases of breast cancer.

A description is given of a method for automatically deriving a Bayesian probability network from CAD based 3D models. This network may be used to match 3D objects to features derived from range images in the presence of uncertainty. The network describes how evidence for subparts of an object should be combined to calculate the evidence for an object. A prototype model based range interpretation system using this method is also presented. Sample results for an object are presented. For this prototype system, sources of evidence include maximum likelihood estimate fits of circular cylinders, planes, and spheres, as well as boundary data (i.e. edges).>

A fundamental group in computer vision is the recovery of three-dimensional shape from image data. While this problem is in general underconstrained, the authors show that it can be simplified in the case where the objects being viewed are generalized cylinders. They consider the class of straight homogeneous generalized cylinders (SHGCs), without any further assumption on the viewing direction or the precise shape of these objects. They present a rigorous mathematical study of the geometry of SHGCs and characterize their Gaussian curvature and occluding contours, and use these results to prove several new invariant properties of the contours of SHGCs. These properties are, in turn, used in two implemented algorithms for recovering SHGC descriptions from image contours. Several examples of segmentation of real images are given. Other applications are also discussed.>

This paper addresses the problem of finding analytically the limbs and cusps of generalized cylinders. Orthographic projections of generalized cylinders whose axis is straight and whose axis is an arbitrary 3D curve are considered in turn. In both cases, the general equations of the limbs and cusps are given. They are solved for three classes of generalized cylinders: solids of revolution, straight homogeneous generalized cylinders whose scaling sweeping rule is a polynomial of degree less than or equal to 5 and generalized cylinders whose axis is an arbitrary 3D curve but the cross section is circular and constant. Examples of limbs and cusps found for each class are given. Extensions and applications of the results presented are discussed.

This paper reports progress in the development of a solid modelling system combining straight homogeneous generalized cylinders through set operations. Two basic components of this system are the modules which compute the set operations between primitives and display the resulting solids using ray tracing. These two modules are also very computationally intensive as they involve a large number of surface-surface and ray-surface intersections computations. We introduce a novel hierarchical representation for straight homogeneous cylinders called Box Tree. The Box Tree is analogous to a Quadtree in parameter space. It is an exact boundary representation which describes the surface of the associated generalized cylinder by a hierarchy of enclosing boxes. We use the Box Tree to efficiently compute the set operations and ray tracing algorithms by localizing the search for intersections to the regions where they may occur. We discuss complexity issues and illustrate the performances of our modelling system on a variety of examples.