Localizing Region-Based Active Contours

©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/TIP.2008.2004611In this paper, we propose a natural framework that allows any region-based segmentation energy to be re-formulated in a local way. We consider local rather than global image statistics and evolve a contour based on local information. Localized contours are capable of segmenting objects with heterogeneous feature profiles that would be difficult to capture correctly using a standard global method. The presented technique is versatile enough to be used with any global region-based active contour energy and instill in it the benefits of localization. We describe this framework and demonstrate the localization of three well-known energies in order to illustrate how our framework can be applied to any energy. We then compare each localized energy to its global counterpart to show the improvements that can be achieved. Next, an in-depth study of the behaviors of these energies in response to the degree of localization is given. Finally, we show results on challenging images to illustrate the robust and accurate segmentations that are possible with this new class of active contour models

Predicting Facebook Continuance Intention: The Roles of Interpersonal and Technology Trust

This paper examines trust’s role in predicting Facebook continuance intention. We examine the relative influence of two types of trusting beliefs including interpersonal-related trust beliefs and technology-related trust beliefs on technology trusting intentions. Interpersonal trusting beliefs include integrity, competence, and benevolence. Technology-related trusting beliefs include three conceptually similar, yet distinct beliefs including reliability, functionality, and helpfulness. We find that college-aged Facebook users’ interpersonal and technology-related beliefs have similar effects on trusting intentions. Thus the two types of beliefs are conceptually and functionally equivalent. Our results also show that trusting intention mediates the effects of trusting beliefs on continuance intentions. This initial study presents future research opportunities to explore the importance of these two types of trusting beliefs in other technology contexts

Effects of Prior Use, Intention, and Habit on IT Continuance Across Sporadic Use and Frequent Use Conditions

This article is motivated by the desire to integrate and expand two literature streams, one that models effects of prior information technology (IT) use and habit strength on continued IT use and another that studies how to apply such models to IT that are used in a characteristically sporadic manner. We find that joint predictions of continuance intention, prior IT use, and habit strength within our research model are superior to subsets of the model across the extended range of usage frequency we studied. However, subsets of the model can also provide reasonable predictions where all measures are not available

Paying Attention to News Briefs about Innovative Technologies

News sources about innovative technologies like Google’s driverless car and Apple’s Siri feature can help potential users evaluate the benefits and risks involved. However, individuals must pay attention to this information before they can make sense of it, and decide to change their technology trusting intention. While other fields investigate attention, no research to date has investigated why people pay attention to news briefs about innovative technologies. We propose four factors based on information processing theory. An exploratory study in which respondents are given a series of news briefs and asked how much they paid attention to them and why, provides support for four of our eight propositions. We find the strongest reasons for paying attention/(disregarding) the news briefs are the positive/(negative) nature of the news brief content characteristics. However, the biggest changes in trust are from positive and negative technology involvement factors

Making and Evaluating Participant Choice in Experimental Research on Information Technology: A Framework and Assessment

Evaluations of participant samples for experiments in information systems research often appear to be informal and intuitive. Appropriate participant choice becomes a more salient issue as the population of information technology professionals and users grows increasingly diverse, and the distribution of relevant characteristics in participant samples such as age, gender, nationality, and experience can often be unrepresentative of the characteristics’ distribution in target populations. In this paper, we present a framework based on widely accepted standards for evaluating participant choice and providing rationale that the choice is appropriate. Using a step-by-step approach, we compare current practice in experimental studies from top information systems journals to this framework. Based on this comparison, we recommend how to improve the treatment of participant choice when evaluating the validity of study inferences and how to discuss the tradeoffs involved in choosing participant samples

A Quantitative and Qualitative Study of Facebook Privacy using the Antecedent-Privacy Concern-Outcome Macro Model

Information privacy is a complex and important phenomenon to understand. Because of this, several recent review articles have integrated findings across various studies and contexts. In this study we investigate information privacy in the online social networking context using the Antecedent-Privacy Concern-Outcome (APCO) Macro Model as the theoretical lens. We use both quantitative and qualitative data collected in a survey of Facebook users. Online social networking provides a rich window into privacy concerns and the resulting behavioral reactions. By analyzing both types of data, we are able to show additional support and insights for our hypotheses tests. These results provide future research opportunities that include modifying the APCO model and refining its constructs to be more context and risk-specific

Do People Trust Facebook as a Technology or as a Person ? Distinguishing Technology Trust from Interpersonal Trust

Several researchers have studied technology trust in terms of the technological artifact of the technology. Two different types of trusting beliefs could apply to websites. First, the trusting beliefs may relate to interpersonal characteristics such as benevolence, competence, and integrity. Second, they may relate to technology characteristics such as helpfulness, functionality, and reliability. Since social networking websites like Facebook may demonstrate either interpersonal trust characteristics or technology trust characteristics, researchers may need to carefully choose the beliefs to model. Thus it is important to not only understand the conceptual meaning of these beliefs, but also whether human and technology trust beliefs of technology trust are distinct. Using data collected from Facebook users, we test alternate factor structures for a measurement model containing three interpersonal trust beliefs and three technology trust beliefs. We find the data fits a firstorder six-factor model the best. This suggests people can distinguish between trust in Facebook’s interpersonal and technology trust characteristics. it also shows they can distinguish between the individual components of these characteristics

Privacy Management Strategies: An Exploratory Cluster Analysis

Online privacy management research related to e-commerce mainly focuses on whether or not to disclose information. Online social networking (OSN) on the other hand, offers a broader set of privacy management strategies. However, how individuals use these OSN strategies has not yet been studied. We survey college students about a popular OSN website and four privacy management strategies: privacy setting use, limiting content disclosure, friend list variety ,and firend list size. We take an exploratory approach using cluster analysis that results in four clusters with varying combinations of privacy management strategies. The findings reveal intriguing differences among the combinations of privacy control strategies. Overall, the findings support the control portfolios approach of Kirsch. Further, we show that each cluster has unique motivations for continued OSN use. Implications for future research are discussed

Interdisciplinary Research and Publication Opportunites in Information Systems and Health Care

Healthcare is a large and growing industry that is experiencing major transformation in its information technology base. IS confronted similar transformations in other industries and developed theories and methods that should prove useful in healthcare applications. In turn, IS may benefit from incorporating knowledge from health informatics, a discipline that studies IT within medical and healthcare contexts. Despite the benefits, it is often a struggle for interdisciplinary researchers in IS and healthcare to publish their work, especially in journals directed toward IS audiences. In this paper, we outline strategies and resources to help ease this publication bottleneck. As a part of our discussion, we identify and categorize journal outlets for interdisciplinary research in IS and healthcare