Basics of qualitative research: Grounded theory procedures and techniques

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

A morphable model for the synthesis of 3D faces

A catalogue record for this book is available from the British Library ISBN 0 521 82347 1 hardback ISBN 0 521 53032 6 paperback Contents List of tables page vii Preface to the second edition ix Preface to the first edition xii 1 Why a global language? 1 What is a global language? 3 What makes a global language? 7 Why do we need a global language? 11 What are the dangers of a global language? 14 Could anything stop a global language? 25 A critical era 27 2 Why English? The historical context 29 Origins 30 America 31 Canada 36 The Caribbean 39 Australia and New Zealand 40 South Africa 43 South Asia 46 Former colonial Africa 49 Southeast Asia and the South Pacific 54 A world view 59 v Contents

English as a global language

On Educational psychology: A cognitive view.

Modern smartphones contain sophisticated sensors to monitor three-dimensional movement of the device. These sensors permit devices to recognize motion gestures - deliberate movements of the device by end-users to invoke commands. However, little is known about best-practices in motion gesture design for the mobile computing paradigm. To address this issue, we present the results of a guessability study that elicits end-user motion gestures to invoke commands on a smartphone device. We demonstrate that consensus exists among our participants on parameters of movement and on mappings of motion gestures onto commands. We use this consensus to develop a taxonomy for motion gestures and to specify an end-user inspired motion gesture set. We highlight the implications of this work to the design of smartphone applications and hardware. Finally, we argue that our results influence best practices in design for all gestural interfaces.

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User-defined motion gestures for mobile interaction

This paper offers a solution to the mode problem in computer sketch/notetaking programs. Conventionally, the user must specify the intended "draw" or "command" mode prior to performing a stroke. This necessity has proven to be a barrier to the usability of pen/stylus systems. We offer a novel Inferred-Mode interaction protocol that avoids the mode hassles of conventional sketch systems. The system infers the user's intent, if possible, from the properties of the pen trajectory and the context of the trajectory. If the intent is ambiguous, the user is offered a choice mediator in the form of a pop-up button. To maximize the fluidity of drawing, the user is entitled to ignore the mediator and continue drawing. We present decision logic for the inferred mode protocol, and discuss subtleties learned in the course of its development. We also present results of initial user trials validating the usability of this interaction design.

Stylus input and editing without prior selection of mode

Recently proposed novel interaction techniques such as cursor jumping [1] and target expansion for tiled arrangements [13] are predicated on an ability to effectively estimate the endpoint of an input gesture prior to its completion. However, current endpoint estimation techniques lack the precision to make these interaction techniques possible. To address a recognized lack of effective endpoint prediction mechanisms, we propose a new technique for endpoint prediction that applies established laws of motion kinematics in a novel way to the identification of motion endpoint. The technique derives a model of speed over distance that permits extrapolation. We verify our model experimentally using stylus targeting tasks, and demonstrate that our endpoint prediction is almost twice as accurate as the previously tested technique [13] at points more than twice as distant from motion endpoint.

Endpoint prediction using motion kinematics

A primary goal of research in usable security and privacy is to understand the differences and similarities between users. While past researchers have clustered users into different groups, past categories of users have proven to be poor predictors of end-user behaviors. In this paper, we perform an alternative clustering of users based on their behaviors. Through the analysis of data from surveys and interviews of participants, we identify five user clusters that emerge from end-user behaviors-Fundamentalists, Lazy Experts, Technicians, Amateurs and the Marginally Concerned. We examine the stability of our clusters through a survey-based study of an alternative sample, showing that clustering remains consistent. We conduct a small-scale design study to demonstrate the utility of our clusters in design. Finally, we argue that our clusters complement past work in understanding privacy choices, and that our categorization technique can aid in the design of new computer security technologies.

Privacy Personas: Clustering Users via Attitudes and Behaviors toward Security Practices

Diagrams are widely used by software engineers to capture the structure and organization of software systems. The Unified Modeling Language (UML) is a commonly-used notation for such diagrams. We have designed and implemented a system for the on-line recognition of hand drawn UML diagrams. Input comes from an electronic whiteboard, a mouse, or a data tablet. A sophisticated segmentation algorithm groups pen strokes into symbols, coping with drawing inaccuracies that are common in hand drawn input. The system is organized around a retargetable kernel which provides a general front end for on-line recognition of any iconic notation. The kernel is extended with UML specific enhancements to segmentation, as well as UML specific glyph recognizers. A simple and intuitive graphical user interface allows the user to correct segmentation and recognition errors. Relatively messy freehand UML drawings are interpreted properly.

Edward Lank

Papers

User-defined motion gestures for mobile interaction

Stylus input and editing without prior selection of mode

Endpoint prediction using motion kinematics

Privacy Personas: Clustering Users via Attitudes and Behaviors toward Security Practices

An interactive system for recognizing hand drawn UML diagrams