62172477
A unified framework for uncertainty propagation in automatic shape tracking
Uncertainty handling plays an important role during shape tracking. We have recently shown that the fusion of measurement information with system dynamics and shape priors greatly improves the tracking performance for very noisy images such as ultrasound sequences [22]. Nevertheless, this approach required user initialization of the tracking process. This paper solves the automatic initialization problem by performing boosted shape detection as a generic measurement process and integrating it in our tracking framework. We show how to propagate the local detection uncertainties of multiple shape candidates during shape alignment, fusion with the predicted shape prior, and fusion with subspace constraints. As a result, we treat all sources of information in a unified way and derive the posterior shape model as the shape with the maximum likelihood. Our framework is applied for the automatic tracking of endocardium in ultrasound sequences of the human heart. Reliable detection and robust tracking results are achieved when compared to existing approaches and inter-expert variations.
14750394
Global models with parametric offsets as applied to cardiac motion recovery
We introduce a new solid shape model formulation that includes built-in offsets from a base global component (e.g. an ellipsoid) which are functions of the global component's parameters. The offsets provide two features. First, they help to form an expected model shape which facilitates appropriate model data correspondences. Second, they scale with the base global model to maintain the expected shape even in the presence of large global deformations. We apply this model formulation to the recovery of 3-D cardiac motion from a volunteer dataset of tagged-MR images. The model instance is a variation of the hybrid volumetric ventriculoid (HVV), a deformable thick-walled ellipsoid model resembling the left ventricle (LV) of the heart. A unique aspect of of implementation is the employment of constant volume constraints when recovering the cardiac motion. In addition, we present a novel geodesic-like prismoidal tessellation of the model which provides for more stable fits.
14869645
Multi-modality model-based registration in the cardiac domain
Recent advances in CT technology have made possible the acquisition of high resolution images of the heart in which important anatomical features such as the coronary vessels are visible. The state of the art in MR Imaging techniques, on the other hand, typically provides lower resolution but can facilitate the differentiation of viable (healthy) cardiac tissue from infarcted (injured) tissue. The registration of CT and MR images of the same heart permit the association of anatomy with function. As an example, given an infarcted region, the coronary vessels responsible for irrigating that region may be isolated and targeted for treatment (e.g., coronary bypass). We demonstrate a software package, PROTEUS, which is capable of registering CT and MR images. Since the manifestation of cardiac tissue in the two modalities differs so greatly we rely on features to perform the matching. Specifically, we employ a model-based approach that relies on segmented contours delineating the inner and outer borders of the left ventricle (LV). Given these contours, our technique is completely automatic.
38069956
Introduction to the Special Issue on Innovative Applications of Computer Vision
11252982
Segmentation of range images as the search for geometric parametric models
Segmentation of range images has long been considered in computer vision as an important but extremely difficult problem. In this paper we present a new paradigm for the segmentation of range images into piecewise continuous surfaces. Data aggregation is performed via model recovery in terms of variable-order bi-variate polynomials using iterative regression. Model recovery is initiated independently in regularly placed seed regions in the image. All the recovered models are potential candidates for the final description of the data. Selection of the models is defined as a quadratic Boolean problem, and the solution is sought by the WTA (winner-takes-all) technique, which turns out to be a good compromise between the speed of computation and the accuracy of the solution. The overall efficiency of the method is achieved by combining model recovery and model selection in an iterative way. Partial recovery of the models is followed by the selection (optimization) procedure and only the “best” models are allowed to develop further.The major novelty of the approach lies in an effective combination of simple component algorithms, which stands in contrast to methods which attempt to solve the problem in a single processing step using sophisticated means. We present the results on several real range images.
5097328
Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours
The problem of segmenting an image into separate regions and tracking them over time is one of the most significant problems in vision. Terzopoulos et al. (1987) proposed an approach to detect the contour regions of complex shapes, assuming a user selected initial contour not very far from the desired solution. We propose to further explore the information provided by the user's selected points and apply an optimal method to detect contours which allows a segmentation of the image. The method is based on dynamic programming (DP), and applies to a wide variety of shapes. It is exact and not iterative. We also consider a multiscale approach capable of speeding up the algorithm by a factor of 20, although at the expense of losing the guaranteed optimality characteristic. The problem of tracking and matching these contours is addressed. For tracking, the final contour obtained at one frame is sampled and used as initial points for the next frame. Then, the same DP process is applied. For matching, a novel strategy is proposed where the solution is a smooth displacement field in which unmatched regions are allowed while cross vectors are not. The algorithm is again based on DP and the optimal solution is guaranteed. We have demonstrated the algorithms on natural objects in a large spectrum of applications, including interactive segmentation and automatic tracking of the regions of interest in medical images. >
15213964
Performance Indicators in a 802.11 WLAN Deployment
Organizations and Institutions across the world are increasingly deploying 802.11 based WLAN (in short Wi-Fi) to have mobility benefits in their operations. However, due to the nature of 802.11 technology, there are more number of challenges for an administrator in ensuring the optimum performance levels for the deployed WLAN compared to a Wired Network. Degraded performance leads to connectivity problems and low data throughput for wireless clients using the Wi-Fi network. In the presented work, we have identified a set of indicators whose values at any point of time signals a possible degradation in WLAN performance. Each of the identified indicators is explained and the behavior of same is illustrated using an example with respect to presence or absence of performance anomalies in a WLAN deployment.
18669821
Managing computing resources in intranets: an electronic commerce perspective
Abstract Intra-organizational networks (intranets) are increasingly being developed for information sharing and collaborative work in geographically dispersed organizations. However, organizations are increasingly realizing that having an intranet in itself may not provide expected increase in productivity and benefits. Intranet resources have to be managed appropriately and with organizational goals in mind for intranets to be a meaningful part of organizational environment. In this paper we provide a framework to manage the resources in the intranets using the concepts of electronic commerce. Specifically, we propose the creation of an electronic organizational unit, intranet Resource Management Unit (iRMU), that manages user requests using a dynamic priority pricing approach. The iRMU integrates a dynamic priority pricing approach with the concepts of topology management, security management, and software-agents based service construction to create a comprehensive resource management environment. The contribution of this paper is to provide a framework that integrates existing technological base with economic pricing approaches to create an economics-embedded intranet resource management approach.
18542805
IT infrastructure in emerging markets: arguing for an end-to-end perspective
To help sustain large-scale pervasive computing in emerging markets, researchers must address unique challenges in the delivery fabric and enterprise backbone. Such challenges present opportunities for high impact innovation. Although most research organizations have focused on developing consumer-facing solutions, we posit that future research must take an end-to-end perspective. That is, researchers must not only consider the front end (such as consumer devices) but also the medium to reach the consumer (for example, the delivery fabric) and the back end (for example, the enterprise backbone) to create an economically sustainable, scalable solution. Although our end-to-end perspective generalizes to all emerging markets, in this article, we mainly discuss the Indian market from which we based our observations.
195894838
Dynamic Access Control Framework Based On Events.
39076736
Designing Intelligent Software Agents for Auctions with Limited Information Feedback
This paper presents analytical, computational, and empirical analyses of strategies for intelligent bid formulations in online auctions. We present results related to a weighted-average ascending price auction mechanism that is designed to provide opaque feedback information to bidders and presents a challenge in formulating appropriate bids. Using limited information provided by the mechanism, we design strategies for software agents to make bids intelligently. In particular, we derive analytical results for the important characteristics of the auction, which allow estimation of the key parameters; we then use these theoretical results to design several bidding strategies. We demonstrate the validity of designed strategies using a discrete event simulation model that resembles the mechanisms used in treasury bills auctions, business-to-consumer (B2C) auctions, and auctions for environmental emission allowances. In addition, using the data generated by the simulation model, we show that intelligent strategies can provide a high probability of winning an auction without significant loss in surplus.