3D display size matters: Compensating for the perceptual effects of S3D display scaling

Abstract Introduction In recent years the consumer electronics market has been flooded with a variety of S3D products, which rely on a variety of display and image segregation technologies. For each display system, the ideal viewing conditions (eg. viewing angle) can be defined in order to obtain the desired 3D experience. SMPTE and THX [1, 2] have provided specific standards and guidelines for the ideal viewing angle for theatre and television. However, screen dimension 1 is an uncontrolled variable since the same content could be displayed on a mobile autostereoscopic device, 3D monitor, HD 3DTV or in a 3D movie theatre. Adapting a S3D film to a variety of screen sizes is necessary for most, if not all, popular movies if the distributors are to maximize their exposure and therefore earnings. However, unlike 2D film the S3D scaling process is complicated by a variety of 1 The range of viewing distances typically used are correlated with the size of the display, with audiences moving closer as screens get smaller. If field of view is constant it is often the distance that is more important. Since they normally co-vary here we will focus on screen size and related disparity scaling issues, but will point out the role of viewing distance in particular when it is warranted. computational and perceptual issues that can significantly impact the audience experience. As outlined below, the existing approaches to scaling S3D content for a variety of delivery form factors can be divided into two main categories: those applied during acquisition and those applied during postproduction or display. The most common strategy is some combination of pre and post-production approaches. However, inevitably some degree of perceptual and geometric distortion will remain. A better understanding of these distortions and their perceptual consequences will provide S3D content creators with insight and context for using sophisticated scaling approaches based on both acquisition and post-production techniques. This paper will review the principal issues related to S3D content scaling, some of the technical solutions available to content makers/ providers and the perceptual consequences for audiences. Stereoscopic Geometry As was shown by Spottiswood in the early 1950's [3], displaying stereoscopic 3D content at different sizes may dramatically influence the audience's S3D experience. Given the interdependence of acquisition and display parameters; most filmmakers, while trying to protect for different screen dimensions will have a target viewing condition when they begin filming. Figures 1 and 2 depict stereoscopic viewing and acquisition geometry, respectivel

Object Association Across Multiple Moving Cameras In Planar Scenes

In this dissertation, we address the problem of object detection and object association across multiple cameras over large areas that are well modeled by planes. We present a unifying probabilistic framework that captures the underlying geometry of planar scenes, and present algorithms to estimate geometric relationships between different cameras, which are subsequently used for co-operative association of objects. We first present a local1 object detection scheme that has three fundamental innovations over existing approaches. First, the model of the intensities of image pixels as independent random variables is challenged and it is asserted that useful correlation exists in intensities of spatially proximal pixels. This correlation is exploited to sustain high levels of detection accuracy in the presence of dynamic scene behavior, nominal misalignments and motion due to parallax. By using a non-parametric density estimation method over a joint domain-range representation of image pixels, complex dependencies between the domain (location) and range (color) are directly modeled. We present a model of the background as a single probability density. Second, temporal persistence is introduced as a detection criterion. Unlike previous approaches to object detection that detect objects by building adaptive models of the background, the foreground is modeled to augment the detection of objects (without explicit tracking), since objects detected in the preceding frame contain substantial evidence for detection in the current frame. Finally, the background and foreground models are used competitively in a MAP-MRF decision framework, stressing spatial context as a condition of detecting interesting objects and the posterior function is maximized efficiently by finding the minimum cut of a capacitated graph. Experimental validation of the method is performed and presented on a diverse set of data. We then address the problem of associating objects across multiple cameras in planar scenes. Since cameras may be moving, there is a possibility of both spatial and temporal non-overlap in the fields of view of the camera. We first address the case where spatial and temporal overlap can be assumed. Since the cameras are moving and often widely separated, direct appearance-based or proximity-based constraints cannot be used. Instead, we exploit geometric constraints on the relationship between the motion of each object across cameras, to test multiple correspondence hypotheses, without assuming any prior calibration information. Here, there are three contributions. First, we present a statistically and geometrically meaningful means of evaluating a hypothesized correspondence between multiple objects in multiple cameras. Second, since multiple cameras exist, ensuring coherency in association, i.e. transitive closure is maintained between more than two cameras, is an essential requirement. To ensure such coherency we pose the problem of object associating across cameras as a k-dimensional matching and use an approximation to find the association. We show that, under appropriate conditions, re-entering objects can also be re-associated to their original labels. Third, we show that as a result of associating objects across the cameras, a concurrent visualization of multiple aerial video streams is possible. Results are shown on a number of real and controlled scenarios with multiple objects observed by multiple cameras, validating our qualitative models. Finally, we present a unifying framework for object association across multiple cameras and for estimating inter-camera homographies between (spatially and temporally) overlapping and non-overlapping cameras, whether they are moving or non-moving. By making use of explicit polynomial models for the kinematics of objects, we present algorithms to estimate inter-frame homographies. Under an appropriate measurement noise model, an EM algorithm is applied for the maximum likelihood estimation of the inter-camera homographies and kinematic parameters. Rather than fit curves locally (in each camera) and match them across views, we present an approach that simultaneously refines the estimates of inter-camera homographies and curve coefficients globally. We demonstrate the efficacy of the approach on a number of real sequences taken from aerial cameras, and report quantitative performance during simulations

The role of groups in smart camera networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (p. 103-111).Recent research in sensor networks has made it possible to deploy networks of sensors with significant local processing. These sensor networks are revolutionising information collection and processing in many different environments. Often the amount of local data produced by these devices, and their sheer number, makes centralised data processing infeasible. Smart camera networks represent a particular challenge in this regard, partly because of the amount of data produced by each camera, but also because many high level vision algorithms require data from more than one camera. Many distributed algorithms exist that work locally to produce results from a collection of nodes, but as this number grows the algorithm's performance is quickly crippled by the resulting exponential increase in communication overhead. This thesis examines the limits this puts on peer-to-peer cooperation between nodes, and demonstrates how for large networks these can only be circumvented by locally formed organisations of nodes. A local group forming protocol is described that provides a method for nodes to create a bottom-up organisation based purely on local conditions. This allows the formation of a dynamic information network of cooperating nodes, in which a distributed algorithm can organise the communications of its nodes using purely local knowledge to maintain its global network performance.(cont.) Building on recent work using SIFT feature detection, this protocol is demonstrated in a network of smart cameras. Local groups with shared views are established, which allow each camera to locally determine their relative position with others in the network. The result partitions the network into groups of cameras with known visual relationships, which can then be used for further analysis.by Jacky Mallett.Ph.D

MediaSync: Handbook on Multimedia Synchronization

This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences