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We develop a systematic approach to the discovery of parallel iterative schemes for solving the shape-from-shading problem on a grid. A standard procedure for finding such schemes is outlined, and subsequently used to derive several new ones. The shape-from-shading problem is known to be mathematically equivalent to a nonlinear first-order partial(More)
—We consider the problem of estimating parameters of a model described by an equation of special form. Specific models arise in the analysis of a wide class of computer vision problems, including conic fitting and estimation of the fundamental matrix. We assume that noisy data are accompanied by (known) covariance matrices characterising the uncertainty of(More)
A method of constrained parameter estimation is proposed for a class of computer vision problems. In a typical application, the parameters will describe a relationship between image feature locations, expressed as an equation linking the parameters and the image data, and will satisfy an ancillary constraint not involving the image data. A salient feature(More)
We consider the problem of metrically reconstructing a scene viewed by a m o ving stereo head. The head comprises two cameras with coplanar optical axes arranged on a lateral rig, each camera being free to vary its angle of vergence. Under various constraints, we derive n o vel explicit forms for the epipolar equation, and show that a static stereo head(More)
The main result of this paper is a procedure for self-calibration of a moving camera from instantaneous optical ow. Under certain assumptions , this procedure allows the ego-motion and some intrinsic parameters of the camera to be determined solely from the instantaneous positions and velocities of a set of image features. The proposed method relies upon(More)
This paper is about tracking people in real-time as they move through the non-overlapping fields of view of multiple video cameras. The paper builds upon existing methods for tracking moving objects in a single camera. The key extension is the use of a stochastic transition matrix to describe people's observed patterns of motion both within and between(More)
Tracking objects in video using the mean shift (MS) technique has been the subject of considerable attention. In this work, we aim to remedy one of its shortcomings. MS, like other gradient ascent optimization methods, is designed to find local modes. In many situations, however, we seek the global mode of a density function. The standard MS tracker assumes(More)
Problems requiring accurate determination of parameters from image-based quantities arise often in computer vision. Two recent, independently developed frameworks for estimating such parameters are the FNS and HEIV schemes. Here, it is shown that FNS and a core version of HEIV are essentially equivalent, solving a common underlying equation via different(More)
The optical flow observed by a moving camera satisfies, in the absence of noise, a special equation analogous to the epipo-lar constraint arising in stereo vision. Computing the ''flow fundamental matrix'' of this equation is an essential prerequisite to undertaking three-dimensional analysis of the flow. This article presents an optimal formulation of the(More)