7 research outputs found

    Focus: A Usable & Effective Approach to OLED Display Power Management

    Get PDF
    Singapore under its Academic Research Funding Tier 2; National Research Foundation (NRF) Singapore under IDM Futures Funding Initiativ

    Learning user interest for image browsing on small-form-factor devices

    No full text
    Mobile devices which can capture and view pictures are becoming increasingly common in our life. The limitation of these small-form-factor devices makes the user experience of image browsing quite different from that on desktop PCs. In this paper, we first present a user study on how users interact with a mobile image browser with basic functions. We found that on small displays, users tend to use more zooming and scrolling actions in order to view interesting regions in detail. From this fact, we designed a new method to detect user interest maps and extract user attention objects from the image browsing log. This approach is more efficient than image-analysis based methods and can better represent users ’ actual interest. A smart image viewer was then developed based on user interest analysis. A second experiment was carried out to study how users behave with such a viewer. Experimental results demonstrate that the new smart features can improve the browsing efficiency and are a good compliment to traditional image browsers

    Using User Saliency For Effective OLED Display Power Management

    Get PDF

    Automatic Mobile Video Remixing and Collaborative Watching Systems

    Get PDF
    In the thesis, the implications of combining collaboration with automation for remix creation are analyzed. We first present a sensor-enhanced Automatic Video Remixing System (AVRS), which intelligently processes mobile videos in combination with mobile device sensor information. The sensor-enhanced AVRS system involves certain architectural choices, which meet the key system requirements (leverage user generated content, use sensor information, reduce end user burden), and user experience requirements. Architecture adaptations are required to improve certain key performance parameters. In addition, certain operating parameters need to be constrained, for real world deployment feasibility. Subsequently, sensor-less cloud based AVRS and low footprint sensorless AVRS approaches are presented. The three approaches exemplify the importance of operating parameter tradeoffs for system design. The approaches cover a wide spectrum, ranging from a multimodal multi-user client-server system (sensor-enhanced AVRS) to a mobile application which can automatically generate a multi-camera remix experience from a single video. Next, we present the findings from the four user studies involving 77 users related to automatic mobile video remixing. The goal was to validate selected system design goals, provide insights for additional features and identify the challenges and bottlenecks. Topics studied include the role of automation, the value of a video remix as an event memorabilia, the requirements for different types of events and the perceived user value from creating multi-camera remix from a single video. System design implications derived from the user studies are presented. Subsequently, sport summarization, which is a specific form of remix creation is analyzed. In particular, the role of content capture method is analyzed with two complementary approaches. The first approach performs saliency detection in casually captured mobile videos; in contrast, the second one creates multi-camera summaries from role based captured content. Furthermore, a method for interactive customization of summary is presented. Next, the discussion is extended to include the role of users’ situational context and the consumed content in facilitating collaborative watching experience. Mobile based collaborative watching architectures are described, which facilitate a common shared context between the participants. The concept of movable multimedia is introduced to highlight the multidevice environment of current day users. The thesis presents results which have been derived from end-to-end system prototypes tested in real world conditions and corroborated with extensive user impact evaluation

    Mobile information system adoption and use: beliefs and attitudes in mobile context

    Get PDF
    During the last decades scholars and practitioners have been interested in the reasons why users either accept or reject Information Systems (IS). Users' perceptions of information technology have mainly been studied from acceptance, success, or usability perspectives. Although these research approaches have provided valuable information, they all have a limited view. Thus, there is a need for an integrated framework that fulfills the gaps between different approaches. In this study the acceptance and use of mobile systems are analyzed by combining the results of different disciplines. The main result of the study is a new model for Mobile IS Adoption and Use (MISAU). It integrates the elements of technology acceptance, information system success, and usability studies into a single model. As information system acceptance must always be analyzed in context of use, MISAU is based on the mobile service supply chain. The main differences between stationary and mobile systems can be found in network performance and usability of mobile devices. MISAU serves as a framework for case studies in which the effects of these special characteristics on users' perceptions are analyzed. The results of the study indicate that the ever-increasing transmission speeds of mobile networks are not alone adequate to increase the use of mobile services. Perceived quality of service is an outcome of multiple factors. The successful implementation of a mobile IS requires high quality in all elements of service supply chain (i.e. end-user devices, networks, and services). The small size of mobile devices is a serious threat to usability - especially to text entry and navigation within an application. Further studies are still needed in these sectors

    Internet on mobiles: evolution of usability and user experience

    Get PDF
    The mobile Internet is no longer a new phenomenon; the first mobile devices supporting web access were introduced over 10 years ago. During the past ten years technology and business infrastructure have evolved and the number of mobile Internet users has increased all over the world. Service user interface, technology and business infrastructure have built a framework for service adaptation: they can act as enablers or as barriers. Users evaluate how the new technology adds value to their life based on multiple factors. This dissertation has its focus in the area of human-computer interaction research and practices. The overall goal of my research has been to improve the usability and the user experience of mobile Internet services. My research has sought answers to questions relevant in service development process. Questions have varied during the years, the main question being: How to design and create mobile Internet services that people can use and want to use? I have sought answers mostly from a human factors perspective, but have also taken the elements form technology and business infrastructure into consideration. In order to answer the questions raised in service development projects, we have investigated the mobile Internet services in the laboratory and in the field. My research has been conducted in various countries in 3 continents: Asia, Europe and North America. These studies revealed differences in mobile Internet use in different countries and between user groups. Studies in this dissertation were conducted between years 1998 and 2007 and show how questions and research methods have evolved during the time. Good service creation requires that all three factors: technology, business infrastructure and users are taken in consideration. When using knowledge on users in decision making, it is important to understand that the different phases of the service development cycle require the different kind of information on users. It is not enough to know about the users, the knowledge about users has to be transferred into decisions. The service has to be easy to use so that people can use it. This is related to usability. Usability is a very important factor in service adoption, but it is not enough. The service has to have relevant content from user perspective. The content is the reason why people want to use the service. In addition to the content and the ease of use, people evaluate the goodness of the service based on many other aspects: the cost, the availability and the reliability of the system for example. A good service is worth trying and after the first experience, is it worth using. These aspects are considered to influence the 'user experience' of the system. In this work I use lexical analysis to evaluate how the words "usability" and "user experience" are used in mobile HCI conference papers during the past 10 years. The use of both words has increased during the period and reflects the evolution of research questions and methodology over time

    Compréhension de contenus visuels par analyse conjointe du contenu et des usages

    Get PDF
    Dans cette thèse, nous traitons de la compréhension de contenus visuels, qu’il s’agisse d’images, de vidéos ou encore de contenus 3D. On entend par compréhension la capacité à inférer des informations sémantiques sur le contenu visuel. L’objectif de ce travail est d’étudier des méthodes combinant deux approches : 1) l’analyse automatique des contenus et 2) l’analyse des interactions liées à l’utilisation de ces contenus (analyse des usages, en plus bref). Dans un premier temps, nous étudions l’état de l’art issu des communautés de la vision par ordinateur et du multimédia. Il y a 20 ans, l’approche dominante visait une compréhension complètement automatique des images. Cette approche laisse aujourd’hui plus de place à différentes formes d’interventions humaines. Ces dernières peuvent se traduire par la constitution d’une base d’apprentissage annotée, par la résolution interactive de problèmes (par exemple de détection ou de segmentation) ou encore par la collecte d’informations implicites issues des usages du contenu. Il existe des liens riches et complexes entre supervision humaine d’algorithmes automatiques et adaptation des contributions humaines via la mise en œuvre d’algorithmes automatiques. Ces liens sont à l’origine de questions de recherche modernes : comment motiver des intervenants humains ? Comment concevoir des scénarii interactifs pour lesquels les interactions contribuent à comprendre le contenu manipulé ? Comment vérifier la qualité des traces collectées ? Comment agréger les données d’usage ? Comment fusionner les données d’usage avec celles, plus classiques, issues d’une analyse automatique ? Notre revue de la littérature aborde ces questions et permet de positionner les contributions de cette thèse. Celles-ci s’articulent en deux grandes parties. La première partie de nos travaux revisite la détection de régions importantes ou saillantes au travers de retours implicites d’utilisateurs qui visualisent ou acquièrent des con- tenus visuels. En 2D d’abord, plusieurs interfaces de vidéos interactives (en particulier la vidéo zoomable) sont conçues pour coordonner des analyses basées sur le contenu avec celles basées sur l’usage. On généralise ces résultats en 3D avec l’introduction d’un nouveau détecteur de régions saillantes déduit de la capture simultanée de vidéos de la même performance artistique publique (spectacles de danse, de chant etc.) par de nombreux utilisateurs. La seconde contribution de notre travail vise une compréhension sémantique d’images fixes. Nous exploitons les données récoltées à travers un jeu, Ask’nSeek, que nous avons créé. Les interactions élémentaires (comme les clics) et les données textuelles saisies par les joueurs sont, comme précédemment, rapprochées d’analyses automatiques des images. Nous montrons en particulier l’intérêt d’interactions révélatrices des relations spatiales entre différents objets détectables dans une même scène. Après la détection des objets d’intérêt dans une scène, nous abordons aussi le problème, plus ambitieux, de la segmentation. ABSTRACT : This thesis focuses on the problem of understanding visual contents, which can be images, videos or 3D contents. Understanding means that we aim at inferring semantic information about the visual content. The goal of our work is to study methods that combine two types of approaches: 1) automatic content analysis and 2) an analysis of how humans interact with the content (in other words, usage analysis). We start by reviewing the state of the art from both Computer Vision and Multimedia communities. Twenty years ago, the main approach was aiming at a fully automatic understanding of images. This approach today gives way to different forms of human intervention, whether it is through the constitution of annotated datasets, or by solving problems interactively (e.g. detection or segmentation), or by the implicit collection of information gathered from content usages. These different types of human intervention are at the heart of modern research questions: how to motivate human contributors? How to design interactive scenarii that will generate interactions that contribute to content understanding? How to check or ensure the quality of human contributions? How to aggregate human contributions? How to fuse inputs obtained from usage analysis with traditional outputs from content analysis? Our literature review addresses these questions and allows us to position the contributions of this thesis. In our first set of contributions we revisit the detection of important (or salient) regions through implicit feedback from users that either consume or produce visual contents. In 2D, we develop several interfaces of interactive video (e.g. zoomable video) in order to coordinate content analysis and usage analysis. We also generalize these results to 3D by introducing a new detector of salient regions that builds upon simultaneous video recordings of the same public artistic performance (dance show, chant, etc.) by multiple users. The second contribution of our work aims at a semantic understanding of fixed images. With this goal in mind, we use data gathered through a game, Ask’nSeek, that we created. Elementary interactions (such as clicks) together with textual input data from players are, as before, mixed with automatic analysis of images. In particular, we show the usefulness of interactions that help revealing spatial relations between different objects in a scene. After studying the problem of detecting objects on a scene, we also adress the more ambitious problem of segmentation
    corecore