The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a novel framework for shape modeling and shape recovery based on ideas developed by Osher & Sethian for interface motion. In this framework, shapes are represented by propagating fronts, whose motion is governed by a “Hamilton-Jacobi” type equation. This equation is written for a function in which the interface is a particular level set. Unknown shapes are modeled by making...
The view lines associated with a family of profile curves of the projection of a surface onto the retina of a moving camera defines a multi-valued vector field on the surface. The integral curves of this field are called epipolar curves and together with a parametrization of the profiles provide a parametrization of regions of the surface. This parametrization has been used in the systematic reconstruction...
Can we say anything general about the distribution of two dimensional views of general three dimensional objects? In this paper we present a first formal analysis of the stability and likelihood of two dimensional views (under weak perspective projection) of three dimensional objects. This analysis is useful for various aspects of object recognition and database indexing. Examples are Bayesian recognition;...
This paper describes a simple construction for building a combinatorial model of a smooth manifold-solid from a labeled figure representing its occluding contour. The motivation is twofold. First, deriving the combinatorial model is an essential intermediate step in the visual reconstruction of solid-shape from image contours. A description of solid-shape consists of a metric and a topological component...
This contribution investigates local differential techniques for estimating optical flow and its derivatives based on the brightness change constraint. By using the tensor calculus representation we build the Taylor expansion of the gray-value derivatives as well as of the optical flow in a spatiotemporal neighborhood. Such a formulation simplifies a unifying framework for all existing local differential...
The computation of the optical flow field from an image sequences requires the definition of constraints on the temporal change of image features. In general, these constraints limit the motion of the body in space and/or of the features on the image plane. In this paper the implications in the use of multiple constraints in the computational schema are considered. It is shown that differential...
This paper discusses the well known problem of structure from motion for the special case of rigid curves. It is already known that it is theoretically possible to recover the motion and thus the structure of a moving 3D rigid curve observed through one camera given some set of derivatives that are defined on the so-called spatio-temporal surface under the most general camera model of perspective...
We derive sufficient conditions on image structure that permits determination of 3-D motion parameters and depth from motion relative a rigid surface in front of the camera. We assume that only the first order spatio-temporal derivative or of the image is given and that the image intensity is continuously differentiable everywhere or that image contours are continuously differentiable. This means...
The Hough Transform is a class of medium-level vision techniques generally recognised as a robust way to detect geometric features from a 2D image. This paper presents two related techniques. First, a new Hough function is proposed based on a Mahalanobis distance measure that incorporates a formal stochastic model for measurement and model noise. Thus, the effects of image and parameter space quantisation...
Junctions of lines or edges are important visual cues in various fields of computer vision. They are characterized by the existence of more than one orientation at one single point, the so called keypoint. In this work we investigate the performance of highly orientation selective functions to detect multiple orientations and to characterize junctions. A quadrature pair of functions is used to detect...
This paper is devoted to an analytical study of extrema curvature evolution through scale-space. Our analytical study allows to get results which show that, from a qualitative point of view, corner evolution in scale-space has the same behavior for planar curves or surfaces. In particular, this analysis, performed with different corner-shape models, shows that, for a two-corner shape, two curvature...
Edge detectors which use a quadratic nonlinearity in the filtering stage are attracting interest in machine vision applications because of several advantages they enjoy over linear edge detectors. However, many important properties of these quadratic or “energy” edge detectors remain unknown. In this paper, we investigate the behavior of quadratic edge detectors under scaling. We consider two cases...
In this work, we present results from a new formulation for determining image velocities from a time-sequence of X-ray projection images of flowing fluid. Starting with the conservation of mass principle, and physics of X-ray projection, we derive a motion constraint equation for projection imaging, a practical special case of which is shown to be the Horn and Schunck's optical flow constraint. We...
The first-order spatial derivatives of optic flow — dilation, shear and rotation — provide powerful information about motion and surface layout. The log-polar sampled image (LSI) is of increasing interest for active vision, and is particularly well-suited to the measurement of local first-order flow. We explain why this is, propose a simple least-squares method for measuring first-order flow in an...
This paper defines a temporal continuity constraint that expresses assumptions about the evolution of 2D image velocity, or optical flow, over a sequence of images. Temporal continuity is exploited to develop an incremental minimization framework that extends the minimization of a non-convex objective function over time. Within this framework this paper describes an incremental continuation method...
This paper describes the analysis of image sequences taken by a T.V. camera mounted on a car moving in usual outdoor sceneries. Because of the presence of shocks and vibrations during the image acquisition, the numerical computation of temporal derivatives is very noisy and therefore differential techniques to compute the optical flow do not provide adequate results. By using correlation based techniques...
We present a method based on Kalman filtering, for image motion estimation. Within Kalman formalism, a motion boundary can be modelled as a jump in the evolution equation of the filter. The detection of such a jump relies on a χ2 statistical test applied to the innovation signal. The optimal estimation of the jump parameters and the compensation of the current estimate are performed using a General...
This paper presents a method for doing motion segmentation for autonomous vehicles which drive on planar surfaces. There are two distinct types of independent motion that may occur within an image sequence taken from a moving vehicle. The first generic type of independent motion is when the projected motion of points on the independent object violate the epipolar constraint. The second case is where...
We present an algorithm based on MRF modelling for motion detection in image sequences and give a modified version for implementation on analog resistive network. Energy minimization is realized by a network relaxing to its state of minimal power dissipation. It takes a few nanoseconds and replaces advantageously time consuming stochastic or suboptimal deterministic relaxation algorithms. The elementary...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.