Light-field imaging is a research field with applicability in a variety of imaging areas including 3D cinema, entertainment, robotics, and any task requiring range estimation. In contrast to binocular or multi-view stereo approaches, capturing light fields means densely observing a target scene through a window of viewing directions. A principal benefit in light-field imaging for range computation is that one can eliminate the error-prone and computationally expensive process of establishing correspondence. The nearly continuous space of observation allows to compute highly accurate and dense depth maps free of matching. Here, we discuss how to structure the imaging system for optimal ranging over a defined volume - what we term a bounded frustum. We detail the process of designing the light-field setup, including practical issues such as camera footprint and component size influence the depth of field, lateral and range resolution. Both synthetic and real captured scenes are used to analyze the depth precision resulting from a design, and to show how unavoidable inaccuracies such as camera position and focal length variation limit depth precision. Finally, inaccuracies may be sufficiently well compensated through calibration and must be eliminated at the outset.
Camera phones are ubiquitous, and consumers have been adopting them faster than any other technology in modern
history. When connected to a network, though, they are capable of more than just picture taking: Suddenly, they gain
access to the power of the cloud. We exploit this capability by providing a series of image-based personal advisory
services. These are designed to work with any handset over any cellular carrier using commonly available Multimedia
Messaging Service (MMS) and Short Message Service (SMS) features. Targeted at the unsophisticated consumer, these
applications must be quick and easy to use, not requiring download capabilities or preplanning. Thus, all application
processing occurs in the back-end system (i.e., as a cloud service) and not on the handset itself. Presenting an image to
an advisory service in the cloud, a user receives information that can be acted upon immediately. Two of our examples
involve color assessment - selecting cosmetics and home décor paint palettes; the third provides the ability to extract
text from a scene. In the case of the color imaging applications, we have shown that our service rivals the advice quality
of experts. The result of this capability is a new paradigm for mobile interactions - image-based information services
exploiting the ubiquity of camera phones.
Selecting cosmetics requires visual information and often benefits from the assessments of a cosmetics expert. In this
paper we present a unique mobile imaging application that enables women to use their cell phones to get immediate
expert advice when selecting personal cosmetic products. We derive the visual information from analysis of camera
phone images, and provide the judgment of the cosmetics specialist through use of an expert system. The result is a new
paradigm for mobile interactions-image-based information services exploiting the ubiquity of camera phones. The
application is designed to work with any handset over any cellular carrier using commonly available MMS and SMS
features. Targeted at the unsophisticated consumer, it must be quick and easy to use, not requiring download capabilities
or preplanning. Thus, all application processing occurs in the back-end system and not on the handset itself. We present
the imaging pipeline technology and a comparison of the services' accuracy with respect to human experts.
Advances in building high-performance camera arrays [1, 12] have opened the opportunity - and challenge - of using
these devices for autostereoscopic display of live 3D content. Appropriate autostereo display requires calibration of these
camera elements and those of the display facility for accurate placement (and perhaps resampling) of the acquired video
stream. We present progress in exploiting a new approach to this calibration that capitalizes on high quality
homographies between pairs of imagers to develop a global optimal solution delivering epipoles and fundamental
matrices simultaneously for the entire system [2]. Adjustment of the determined camera models to deliver minimal
vertical misalignment in an epipolar sense is used to permit ganged rectification of the separate streams for transitive
positioning in the visual field. Individual homographies [6] are obtained for a projector array that presents the video on a
holographically-diffused retroreflective surface for participant autostereo viewing. The camera model adjustment means
vertical epipolar disparities of the captured signal are minimized, and the projector calibration means the display will
retain these alignments despite projector pose variations. The projector calibration also permits arbitrary alignment
shifts to accommodate focus-of-attention vengeance, should that information be available.
Our purpose in this paper is to describe new techniques for high-resolution range sensing and dynamic vehicle localization. An emphasis of the work is rapid processing, with data redundancy, rather than complex analysis, being used to ensure high quality range estimates. Two aspects of the work are presented here. The first is the use of spatiotemporal consistency filtering to verify range estimates, and the second is the development of a fast registration method that dynamically solves for position and orientation of the platform from stereo range and motion tracking estimates. These methods will enable us to integrate range information over time into a consistent local 3D map.
Three-dimensional biomedical data obtained through tomography provide exceptional views of biological anatomy. While visualization is one of the primary purposes for obtaining these data, other more quantitative and analytic uses are possible. These include modeling of tissue properties and interrelationships, simulation of physical processes, interactive surgical investigation, and analysis of kinematics and dynamics. As an application of our research in modeling tissue structure and function, we have been working to develop interactive and automated tools for studying joint geometry and kinematics. We focus here on discrimination of morphological variations in the foot and determining the implications of these on both hominid bipedal evolution and physical therapy treatment for foot disorders.
3D biomedical data obtained through tomography provide exceptional views of the interior structure of biological material. While visualization is one of the primary purposes for obtaining these data, other more sophisticated uses are possible. These include simulation of physical processes, interactive surgical investigation, modeling of tissue interrelationships, and analysis of dynamics. Visualization is merely the first contribution of computers to the display and analysis of these image data. Techniques are being developed to facilitate such advanced uses of 3D and 4D tomographic data.
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