Learning the Roots of Visual Domain Shift

In this paper we focus on the spatial nature of visual domain shift, attempting to learn where domain adaptation originates in each given image of the source and target set. We borrow concepts and techniques from the CNN visualization literature, and learn domainnes maps able to localize the degree of domain specificity in images. We derive from these maps features related to different domainnes levels, and we show that by considering them as a preprocessing step for a domain adaptation algorithm, the final classification performance is strongly improved. Combined with the whole image representation, these features provide state of the art results on the Office dataset.Comment: Extended Abstrac

CleanGraph - Graph viewing and editing for family trees and UML class diagrams

Traditionally, different types of diagrams are used to represent varying types of data in a fast and easy way to read. Their usage includes describing systems, understanding their features and presenting how different parts are interconnected, making them useful for many applications. Unfortunately, as the complexity of the data showed increases, so does the complexity of the diagram, making it more difficult to read and interpret. Since interactions are usually limited to panning and zooming, there is room for improvement with more interaction and different input methods. The goal is to tackle these issues in two types of diagrams -- Family Trees (FT) and Universal Modeling Language (UML) class diagrams. To achieve this, a new platform will be created, capable of generating diagrams and displaying them in a way where overlapping and unrelated data is minimised alongside having better methods for interacting with and manipulating information. These diagrams will prioritise visual clarity by grouping together elements with relevant or important information, as well as having new ways of interaction, such as selecting elements to receive more information and manually grouping them to better explore the data. Guaranteeing the viability of the solution will require two main issues to be addressed: (1) Defining a fitting diagram disposition and why it is the more advantageous; (2) Understanding the best way to create interactions with diagrams while making it intuitive and keeping them readable. Finding the best platform for the solution to reach its intended audience while providing the desired ease of use is one of the priorities. The evaluation of this work will be attained through previously defined metrics, to ensure that the generated diagram is adequate. The quality of the diagrams will be defined by characteristics such as overlapping connections between elements, related or unrelated data of adjacent elements to the selected one and the amount of displayed data at once. The result of the proposal aims to give a better tool to users seeking improved methods to view their ancestry data, as well as software architects, project managers and system analysts, who would benefit from a better platform for system representation. The developed features can help them convey their ideas easily to developers or anyone interested in the data represented, improving simplicity, workflow and potentially bringing new and improved methods of viewing and displaying information in these areas

Gesture Recognition and Control Part 1 - Basics, Literature Review & Different Techniques

This Exploratory paper series reveals the technological aspects of Gesture Controlled User Interface (GCUI), and identifies trends in technology, application and usability. It is found that GCUI now affords realistic opportunities for specific application are as, and especially for use rs who are uncomfortable with more commonly used input devices. It further explored collated chronograph research information on which covers the past research work in Literature Review . Researchers investigated different types of gestures, its uses, applic ations, technology, issues and results from existing research

Index to 1984 NASA Tech Briefs, volume 9, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1984 Tech B Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Ability-Based Methods for Personalized Keyboard Generation

This study introduces an ability-based method for personalized keyboard generation, wherein an individual's own movement and human-computer interaction data are used to automatically compute a personalized virtual keyboard layout. Our approach integrates a multidirectional point-select task to characterize cursor control over time, distance, and direction. The characterization is automatically employed to develop a computationally efficient keyboard layout that prioritizes each user's movement abilities through capturing directional constraints and preferences. We evaluated our approach in a study involving 16 participants using inertial sensing and facial electromyography as an access method, resulting in significantly increased communication rates using the personalized keyboard (52.0 bits/min) when compared to a generically optimized keyboard (47.9 bits/min). Our results demonstrate the ability to effectively characterize an individual's movement abilities to design a personalized keyboard for improved communication. This work underscores the importance of integrating a user's motor abilities when designing virtual interfaces.Comment: 20 pages, 7 figure

Effective Gesture Based Framework for Capturing User Input

Computers today aren't just confined to laptops and desktops. Mobile gadgets like mobile phones and laptops also make use of it. However, one input device that hasn't changed in the last 50 years is the QWERTY keyboard. Users of virtual keyboards can type on any surface as if it were a keyboard thanks to sensor technology and artificial intelligence. In this research, we use the idea of image processing to create an application for seeing a computer keyboard using a novel framework which can detect hand gestures with precise accuracy while also being sustainable and financially viable. A camera is used to capture keyboard images and finger movements which subsequently acts as a virtual keyboard. In addition, a visible virtual mouse that accepts finger coordinates as input is also described in this study. This system has a direct benefit of reducing peripheral cost, reducing electronics waste generated due to external devices and providing accessibility to people who cannot use the traditional keyboard and mouse