A new generation of simple, affordable and easy to use tools has led to what has been called the "democratization of publishing". Anyone with a camera has become a "photographer", with a keyboard an "author", a microphone a "podcaster", etc. As the means for production and distribution of content have become readily accessible, the most valuable inelastic commodity has become attention. In this talk we will describe both how Yahoo has been working to lower barriers to participation and turn every "consumer" into a "creator", but also how we are using data mining techniques to help identify and leverage high-value content. Yahoo! is creating systems that engender mass participation but also that allow the "cream to rise" by ensuring that every user of the system creates value in his or her wake. Examples from widely available real world products (such as Flickr, Yahoo! Answers, del.icio.us, upcoming.org, etc.) will be used as illustrations.

No abstract available.

A recursive estimation technique for recovering the 3-D motion and pointwise structure of an object is presented. It is based on the use of relative orientation constraints in a local coordinate frame. By carefully formulating the problem to propagate all constraints and to use the minimal number of parameters, an estimator is obtained which is remarkably accurate, stable, and fast-conveying. Numerous experiments using both real and synthetic data demonstrate structure recovery with a typical error of 1.5% and typical motion recovery errors of 1% in translation and 2/spl deg/ in rotation.>

Interactive graphics systems that are driven by visual input are discussed. The underlying computer vision techniques and a theoretical formulation that addresses issues of accuracy, computational efficiency, and compensation for display latency are presented. Experimental results quantitatively compare the accuracy of the visual technique with traditional sensing. An extension to the basic technique to include structure recovery is discussed.>

The elastic properties of real materials provide constraint on the types of non-rigid motion that can occur, and thus allow overconstrained estimates of 3-D non-rigid motion from optical flow data. It is shown that by modeling and simulating the physics of non-rigid motion it is possible to obtain good estimates of both object shape and velocity. Examples using grey-scale and X-ray imagery are presented, including an example of tracking a complex articulated figure.>

A technique for image compression is based on a very simple type of iterative fractal. A wavelet transform (quadrature mirror filter pyramid) is used to decompose an image into bands containing information from different scales (spatial frequencies) and orientations. The conditional probabilities between these different scale bands are then determined, and used as the basis for a predictive coder. The wavelet transform's various scale and orientation bands have a great deal of redundant, self-similar structure in the form of multi-modal conditional probabilities, so that linear predictors perform poorly. A simple histogram method is used to determine the multi-modal conditional probabilities between scales. The resulting predictive coder is easily integrated into existing subband coding schemes.>

The authors introduce a physically correct model of elastic nonrigid motion. This model is based on the finite element method, but decouples the degrees of freedom by breaking down object motion into rigid and nonrigid vibration or deformation modes. The result is an accurate representation for both rigid and nonrigid motion that has greatly reduced dimensionality, capturing the intuition that nonrigid motion is normally coherent and not chaotic. Because of the small number of parameters involved, this representation is used to obtain accurate overstrained estimates of both rigid and nonrigid global motion. It is also shown that these estimates can be integrated over time by use of an extended Kalman filter, resulting in stable and accurate estimates of both three-dimensional shape and three-dimensional velocity. The formulation is then extended to include constrained nonrigid motion. Examples of tracking single nonrigid objects and multiple constrained objects are presented.>

We describe a real-time solid modeling system that is based on the physical analogy of forming clay by applying forces. The system is implemented by simulating real materials as they react to user-supplied forces. Unlike other physically-based modeling approaches, the Thingworld system allows the user to restrict forming action to simple global deformations during the initial roughing in phase of modeling, and then later concern themselves with detailing. The Thingworld system also allows users to automatically model existing objects by using measurements taken from the object's surface. These measurements are used to generate artificial forces that mold the computer model much as a human would mold a clay model. Timed examples for constructing solid models are shown.