We present a vision system for the 3-D model-based tracking of unconstrained human movement. Using image sequences acquired simultaneously from multiple views, we recover the 3-D body pose at each time instant without the use of markers. The pose recovery problem is formulated as a search problem

Pose space deformation generalizes and improves upon both shape interpolation and common skeleton-driven deformation techniques. This deformation approach proceeds from the observation that several types of deformation can be uniformly represented as mappings from a pose space, defined by either

desire loses some of its appeal. Direct reports of subjective well-being may have a useful role in the measurement of consumer preferences and social welfare, if they can be done in a credible way. Indeed, economists have already made much use of subjective well-being data. From 2001 to 2005, more than

We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor prior labelling of body parts in the image. Instead, it recovers pose by direct nonlinear regression against shape

of shape context matching in conjunction with a kinematic chain-based deformation model. Assuming that there is a stored view sufficiently similar in configuration and pose, the correspondence process will succeed. The locations of the body joints are then transferred from the exemplar view to the test

Details in mesh animations are difficult to generate but they have great impact on visual quality. In this work, we demonstrate a practical software system for capturing such details from multi-view video recordings. Given a stream of synchronized video images that record a human performance from

, in order to acquire the 3D shape of the body parts, we present a new algorithm which selectively integrates the (segmented by the HBPIS) apparent contours, from three mutually orthogonal views. The effectiveness of the approach is demonstrated through a series of experiments, where a subject performs a set

, over 33 % of the time, it selects peers along paths that are within a single autonomous system (AS). Further, we find that our system locates peers along paths that have two orders of magnitude lower latency and 30 % lower loss rates than those picked at random, and that these high-quality paths can

mechanics, measure-differential inclu- sions, complementarity problems AMS subject classifications. Primary, 70E55; Secondary, 70F40, 74M PII. S0036144599360110 Rigid Bodies and Friction. Rigid bodies are bodies that cannot deform. They can translate and rotate, but they cannot change their shape. From

reconstruction from multiple receiver data. Using the framework of linear algebra, two different reconstruction strategies have been derived. In their general forms the resulting formulae hold for arbitrary sampling patterns in k-space. A detailed discussion is dedicated to the most practical case, namely