32,211 research outputs found

    Pervasive and standalone computing: The perceptual effects of variable multimedia quality.

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    The introduction of multimedia on pervasive and mobile communication devices raises a number of perceptual quality issues, however, limited work has been done examining the 3-way interaction between use of equipment, quality of perception and quality of service. Our work measures levels of informational transfer (objective) and user satisfaction (subjective)when users are presented with multimedia video clips at three different frame rates, using four different display devices, simulating variation in participant mobility. Our results will show that variation in frame-rate does not impact a user’s level of information assimilation, however, does impact a users’ perception of multimedia video ‘quality’. Additionally, increased visual immersion can be used to increase transfer of video information, but can negatively affect the users’ perception of ‘quality’. Finally, we illustrate the significant affect of clip-content on the transfer of video, audio and textual information, placing into doubt the use of purely objective quality definitions when considering multimedia presentations

    Anahita: A System for 3D Video Streaming with Depth Customization

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    Producing high-quality stereoscopic 3D content requires significantly more effort than preparing regular video footage. In order to assure good depth perception and visual comfort, 3D videos need to be carefully adjusted to specific viewing conditions before they are shown to viewers. While most stereoscopic 3D content is designed for viewing in movie theaters, where viewing conditions do not vary significantly, adapting the same content for viewing on home TV-sets, desktop displays, laptops, and mobile devices requires additional adjustments. To address this challenge, we propose a new system for 3D video streaming that provides automatic depth adjustments as one of its key features. Our system takes into account both the content and the display type in order to customize 3D videos and maximize their perceived quality. We propose a novel method for depth adjustment that is well-suited for videos of field sports such as soccer, football, and tennis. Our method is computationally efficient and it does not introduce any visual artifacts. We have implemented our 3D streaming system and conducted two user studies, which show: (i) adapting stereoscopic 3D videos for different displays is beneficial, and (ii) our proposed system can achieve up to 35% improvement in the perceived quality of the stereoscopic 3D content

    LAPSE: Low-Overhead Adaptive Power Saving and Contrast Enhancement for OLEDs

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    Organic Light Emitting Diode (OLED) display panels are becoming increasingly popular especially in mobile devices; one of the key characteristics of these panels is that their power consumption strongly depends on the displayed image. In this paper we propose LAPSE, a new methodology to concurrently reduce the energy consumed by an OLED display and enhance the contrast of the displayed image, that relies on image-specific pixel-by-pixel transformations. Unlike previous approaches, LAPSE focuses specifically on reducing the overheads required to implement the transformation at runtime. To this end, we propose a transformation that can be executed in real time, either in software, with low time overhead, or in a hardware accelerator with a small area and low energy budget. Despite the significant reduction in complexity, we obtain comparable results to those achieved with more complex approaches in terms of power saving and image quality. Moreover, our method allows to easily explore the full quality-versus-power tradeoff by acting on a few basic parameters; thus, it enables the runtime selection among multiple display quality settings, according to the status of the system

    User Preference in Detail-Enhancement Adjustments for Images Captured by Camera Phones

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    Most smartphones now come with an integrated camera. Such a smartphone is called a camera phone. Popularity of camera phones is rising and it is expected that 87.8% of United States population will possess camera phones by year 2020 (Euromonitor International, 2017). A camera phone’s workflow for capturing, editing, and sharing images on social media has become very efficient. Its ease of use, accessibility, and automatic exposure settings to capture an image has contributed to its popularity. Camera phones are more compact and convenient than professional DSLR cameras. The popularity of this technology has created a need to study and evaluate image quality of photographs from the camera phone. Numerous image-editing applications and adjustments are available to edit these images on the phone itself. Previous studies have shown the reasons why people like to edit their images captured by camera phones (Bakhshi et al., 2014; Bakhshi et al., 2015). This psychophysical study aims to determine the preference related to detail-enhancement adjustments for images captured by camera phones. The image contents used in this study are selfies and food images. Images possessing two levels of high and low ISO were evaluated. The stimuli for the psychophysical experiment were created by editing these images with clarity, contrast and sharpness adjustments. By recording participants’ response and analyzing the data, observers’ preference were determined for different detail-enhancement (DE) adjustments and content of images captured by camera phones. Results showed that the preference for detail-enhancement adjustments was subjective and varied by both person and image. Participants preferred low ISO DE images more than high ISO DE images. Overall, only slight preferences were observed between images possessing different DE adjustments, DE levels and contents, but a significant preference was not observed in any of these variables

    Image Processing for Machine Vision Applications

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    L'abstract Ăš presente nell'allegato / the abstract is in the attachmen

    glueTK: A Framework for Multi-modal, Multi-display Interaction

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    This thesis describes glueTK, a framework for human machine interaction, that allows the integration of multiple input modalities and the interaction across different displays. Building upon the framework, several contributions to integrate pointing gestures into interactive systems are presented. To address the design of interfaces for the wide range of supported displays, a concept for transferring interaction performance from one system to another is defined
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