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Acivs 2005 Abstracts
Invited papers
Paper 106: A system approach towards 3D-in-the-box
As early as the 1920s, TV pioneers dreamed of developing high-definition three-dimensional color TV, as only this would provide the most natural viewing experience. The early black-and-white prototypes have evolved into high-quality color TV, but the hurdle of 3D-TV still remains. From a commercial point of view, 3D-TV can only be introduced successfully, if both 3D content and 3D displays are widely available at the same time. To circumvent this chicken and egg problem, we have designed algorithms that automatically generates depth information for legacy 2D video inside a consumer device.
Information present in 2D video sequences is often incomplete. In general a geometrically correct depth map cannot be reconstructed. However, qualitative depth cues such as focus and motion, are often present. By combining these physical depth cues with image heuristics, qualitative depth maps can be generated. In our system-approach, we have designed a matching lenticular 3D display, that emits multiple views in discrete directions. These views can be rendered out of the existing 2D images and the calculated depth maps.
A real-time PC-based demonstrator of the "3D-in-the-box" system will be shown.
Paper 108: Processing Challenges in Intelligent Video Adaptation
Multimedia data and services are nowadays omnipresent in our society. These services, especially those involving communications, engage technology with its associated limitations as well as the human users who also have associated limitations, or more generally speaking characteristics and preferences. In this context, the service goal is typically maximizing 'quality of service' for the available resources or minimizing the required resources for a prescribed quality of service. The growing heterogeneity of networks, terminals and users and the increasing availability and usage of multimedia content have been raising the relevance of content adaptation technologies able to fulfill the needs associated to all usage conditions without multiplying the number of versions available for the same piece of content while simultaneously maximizing user satisfaction.
In a heterogeneous world, the delivery path for multimedia content to a multimedia terminal is not straightforward. The notion of Universal Multimedia Access (UMA) calls for the provision of different presentations of the same information, with more or less complexity, suiting different usage environments (i.e., the context) in which the content will be consumed; for this purpose, multimedia content has to be adapted either off-line or in real-time.
While universal multimedia adaptation is still in its infancy it has already become clear that, as delivery technology evolves, the human factors associated with multimedia consumption assume an increasing importance. In particular, the importance of the user rather than the terminal as the final point in the multimedia consumption chain is becoming clear. We are starting to speak about Universal Multimedia Experiences (UME) which provide the users with adapted, informative (in the sense of cognition), and exciting (in the sense of feelings) experiences. Following the same trends, the notion of 'quality of service' has to evolve to something more encompassing like 'quality of experience' where user satisfaction considers not only the sensorial and perceptual dimensions but also the important emotional dimension.
While the current vision of the video adaptation process sees it mostly conditioned by the resources available, especially in terms of networks and devices, this is not always the case since the maximization of user satisfaction may require some adaptation processing even if there are no resource constraints. Here the driving force for adaptation would not be the 'resource constraints' part of the equation but the 'satisfaction maximization' part of it. Content and usage environment (or context) descriptions are central to video adaptation since they provide information that can control a suitable adaptation process.
This talk will address the processing challenges in advanced, intelligent video adaptation. After analyzing the major motivations for video adaptation, the talk will discuss the major processes involved in video adaptation from content retrieval to transcoding, transmoding and semantic filtering.
Paper 109: High Resolution Images from a Sequence of low Resolution Observations. A Bayesian perspective
Super resolution of images and video is the research area devoted to the problem of obtaining a high resolution (HR) image or sequences of HR images from a set of low resolution (LR) observations. The LR images are under- sampled and they are acquired either by multiple sensors imaging a single scene or by a single sensor imaging the scene over a period of time
The field of super-resolution processing for uncompressed and compressed low resolution image sequences is surveyed. The introduction of motion vectors, observation noise and additional redundancies within the image sequence make this problem fertile ground for novel processing methods. In conducting this survey though, we develop and present all techniques within the Bayesian framework. This adds consistency to the presentation and facilitates comparison between the different methods.
We first describe the models used in the literature to relate the HR image we want to estimate to the observed LR images. Then we examine the available prior information on the original high resolution image intensities and displacement values. Next we discuss solutions for the super-resolution problem and provide examples of several approaches. Finally, we consider future research directions as well as areas of application.