As Augmented Reality television gains momentum, it is important to understand whether cultural differences among viewers favor different expectations and preferences for immersion in such new television environments. A previous study documented the preferences of 172 participants from various European countries for twenty application scenarios for ARTV, such as virtual objects coming out of the TV screen into the room. In this work, we conduct an empirical generalization of this previous study to understand potential cultural differences in users’ preferences for and expectations of ARTV. To this end, we report insights from data collected from a sample of 147 participants from China, which we compare against the preferences expressed by the participants from Europe from the original study. Our findings reveal similarities, but also differences in terms of expectations of ARTV across the two cultural groups. We draw implications for future research on culturally-aware augmentations of the television watching experience.

We examine users' preferences for Augmented Reality for television and report findings from an exploratory study with 172 participants we conducted to understand the perceived value of twenty distinct AR-TV scenarios. We connect our findings to participants' overall perceptions of and experience with AR technology as well as to their self-reported television watching behavior. Our results reveal high perceived value for AR-TV scenarios involving interactive content, wall-sized and room-sized video projections, multiple perspectives of the same movie scene, and for virtual objects coming out of the TV screen into the room. Other scenarios, such as live video of remote friends watching the same broadcast or multiple virtual channels displayed around the TV screen were rated less valuable.

We present a method for deriving a parametric description of a conic section (quadratic curve) in an image from the moments of the image with respect to several specially-constructed kernel functions. In contrast to Hough-transform-type methods, the moment approach requires no large accumulator array. Judicious implementation allows the parameters to be determined using five multiplication operations and six addition operations per pixel. The use of moments renders the calculation robust in the presence of high-frequency noise or texture and resistant to small-scale irregularities in the edge. Our method is generalizable to more complex classes of curves with more parameters as well as to surfaces in higher dimensions.

We present a method of locating edges in JPEG-coded images which operates in frequency space on the DCT coefficients. Applied to the quantized DCT coefficients of a block containing a straight edge, the method yields an equation for the edge in a fraction of the operations needed to dequantize and transform the coefficents to pixel values. As a sample application of this method, we present a technique for alleviating ringing artifacts in JPEG-coded images.

The method of custom-built moments allows location of step edges in an image in parametric form, as an equation ax+by=c, using a customizable mask of almost any desired shape, or moment functions adapted to calculation in a particular basis. We adapt this method to the problem of locating both thin lines and roof edges in parametric form.

We present a general construction of functions whose moments serve to locate and parametrize step edges within an image. Previous use of moments to locate edges was limited to functions supported on a circular region, but our method allows the use of "custom-designed" functions supported on circles, rectangles, or any desired shape, and with graphs whose shape may be chosen with great freedom. We present analyses of the sensitivity of our method to pixelization errors or discrepancy between the image and an idealized edge model. The parametric edge description yielded by our method makes it especially suitable as a component of wedgelet image coding.

We introduce the eidochromatic transform as a tool for improved lossy coding of color images. Many current image-coding formats (such as JPEG 2000) utilize both a color-component transform (relating values of different image components at a single location) and a wavelet or other spatial transform (relating values of a single-image component at proximate, but different image locations). The eidochromatic transform further reduces redundancy by relating image values simultaneously across color components and in the two spatial dimensions. Our approach is to introduce an additional transform step following the color-component and spatial transforms. In tests, this step reduced the overall static entropy of the chrominance components of quantized transformed images by up to 40% or more. Combined with JPEG 2000's modeling and coding method, the eidochromatic transform was found to reduce the size of lossily coded color images by up to 27% overall.