1937169
Camera calibration with one-dimensional objects
Camera calibration has been studied extensively in computer vision and photogrammetry and the proposed techniques in the literature include those using 3D apparatus (two or three planes orthogonal to each other or a plane undergoing a pure translation, etc.), 2D objects (planar patterns undergoing unknown motions), and 0D features (self-calibration using unknown scene points). Yet, the paper proposes a new calibration technique using 1D objects (points aligned on a line), thus filling the missing dimension in calibration. In particular, we show that camera calibration is not possible with free-moving 1D objects, but can be solved if one point is fixed. A closed-form solution is developed if six or more observations of such a 1D object are made. For higher accuracy, a nonlinear technique based on the maximum likelihood criterion is then used to refine the estimate. Singularities have also been studied. Besides the theoretical aspect, the proposed technique is also important in practice especially when calibrating multiple cameras mounted apart from each other, where the calibration objects are required to be visible simultaneously.
5858737
A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry
Abstract This paper proposes a robust approach to image matching by exploiting the only available geometric constraint, namely, the epipolar constraint. The images are uncalibrated, namely the motion between them and the camera parameters are not known. Thus, the images can be taken by different cameras or a single camera at different time instants. If we make an exhaustive search for the epipolar geometry, the complexity is prohibitively high. The idea underlying our approach is to use classical techniques (correlation and relaxation methods in our particular implementation) to find an initial set of matches, and then use a robust technique—the Least Median of Squares (LMedS)—to discard false matches in this set. The epipolar geometry can then be accurately estimated using a meaningful image criterion. More matches are eventually found, as in stereo matching, by using the recovered epipolar geometry. A large number of experiments have been carried out, and very good results have been obtained. Regarding the relaxation technique, we define a new measure of matching support, which allows a higher tolerance to deformation with respect to rigid transformations in the image plane and a smaller contribution for distant matches than for nearby ones. A new strategy for updating matches is developed, which only selects those matches having both high matching support and low matching ambiguity. The update strategy is different from the classical “winner-take-all”, which is easily stuck at a local minimum, and also from “loser-take-nothing”, which is usually very slow. The proposed algorithm has been widely tested and works remarkably well in a scene with many repetitive patterns.
29303828
Parameter estimation techniques: a tutorial with application to conic fitting
Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear least-squares (pseudo-inverse and eigen analysis); orthogonal least-squares; gradient-weighted least-squares; bias-corrected renormalization; Kalman filtering; and robust techniques (clustering, regression diagnostics, M-estimators, least median of squares). Particular attention has been devoted to discussions about the choice of appropriate minimization criteria and the robustness of the different techniques. Their application to conic fitting is described.
1150626
A Flexible New Technique for Camera Calibration
We propose a flexible technique to easily calibrate a camera. It only requires the camera to observe a planar pattern shown at a few (at least two) different orientations. Either the camera or the planar pattern can be freely moved. The motion need not be known. Radial lens distortion is modeled. The proposed procedure consists of a closed-form solution, followed by a nonlinear refinement based on the maximum likelihood criterion. Both computer simulation and real data have been used to test the proposed technique and very good results have been obtained. Compared with classical techniques which use expensive equipment such as two or three orthogonal planes, the proposed technique is easy to use and flexible. It advances 3D computer vision one more step from laboratory environments to real world use.
206417245
Estimation of Displacements from Two 3-D Frames Obtained From Stereo
A method for estimating 3D displacements from two stereo frames is presented. It is based on the hypothesize-and-verify paradigm used to match 3D line segments between the two frames. In order to reduce the complexity of the method, an assumption is made that objects are rigid. The formulate a set of complete rigidity constraints for 3D line segments and integrate the uncertainty of measurements in this formation. The hypothesize-and-verify stages of the method use an extended Kalman filter to produce estimates of the displacements and of their uncertainty. The algorithm is shown to work on indoor and natural scenes. It is also shown to be easily extended to the case in which several mobile objects are present. The method is quite robust, fast, and has been thoroughly tested on hundreds of real stereo frames. >
1727845
Estimating the Fundamental Matrix by Transforming Image Points in Projective Space
This paper proposes a novel technique for estimating the fundamental matrix by transforming the image points in projective space. We therefore only need to perform nonlinear optimization with one parameterization of the fundamental matrix, rather than considering 36 distinct parameterizations as in previous work. We also show how to preserve the characteristics of the data noise model from the original image space.
5573915
Head pose determination from one image using a generic model
We present a new method for determining the pose of a human head from its 2D image. It does not use any artificial markers put on a face. The basic idea is to use a generic model of a human head, which accounts for variation in shape and facial expression. Particularly, a set of 3D curves are used to model the contours of eyes, lips and eyebrows. A technique called iterative closest curve matching (ICC) is proposed, which aims at recovering the pose by iteratively minimizing the distances between the projected model curves and their closest image curves. Because curves contain richer information (such as curvature and length) than points, ICC is both more robust and more efficient than the well-known iterative closest point matching techniques (ICP). Furthermore, the image can be taken by a camera with unknown internal parameters, which can be recovered by our technique thanks to the 3D model. Preliminary experiments show that the proposed technique is promising and that an accurate pose estimate can be obtained from just one image with a generic head model.
5888722
The transformation graph Gxyz when xyz=-++
The transformation graph G^-^+^+ of G is the graph with vertex set V(G)@?E(G) in which the vertex x and y are joined by an edge if one of the following conditions holds: (i) x,y@?V(G), and x and y are not adjacent in G, (ii) x,y@?E(G), and x and y are adjacent in G, (iii) one of x and y is in V(G) and the other is in E(G), and they are incident in G. In this paper, it is shown that for two graphs G and G^', G^-^+^+@?G^'^-^+^+ if and only if G@?G^'. Simple necessary and sufficient conditions are given for G^-^+^+ to be planar and hamiltonian, respectively. It is also shown that for a graph G, the edge-connectivity of G^-^+^+ is equal to its minimum degree. Two related conjectures and some research problems are presented.
1313086
Image-based surface detail transfer
Changing an object's appearance by adding geometric details is desirable in many real-world applications. Bump mapping has acted as an alternative to adding geometrical details, to an otherwise smooth object. But constructing visually interesting bump maps requires practice and artistic skills. Computer vision techniques have helped for modeling real-world objects and their surface details. In our approach, for cases where we only want to transfer geometrical details from one object to another, we might not need to explicitly compute 3D structures. In particular, our novel technique captures the geometrical details of an object from a single image in a way that is independent of the object's reflectance property. We can then transfer geometrical details to another surface, producing the appearance of a new surface with added geometrical details while preserving the object's reflectance property. Our method's advantages are that it's simple to implement, requires only a single image for each object, and produces effective results.
37643061
Adjacent strong edge coloring of graphs
Abstract For a graph G ( V , E ), if a proper k -edge coloring ƒ is satisfied with C ( u ) ≠ C ( v ) for uv ∈ E ( G ), where C(u) = {ƒ(uv) | uv ∈ E} , then ƒ is called k-adjacent strong edge coloring of G , is abbreviated k-ASEC , and χ ′ as ( G ) = min { k | k - ASEC of G } is called the adjacent strong edge chromatic number of G . In this paper, we discuss some properties of χ′ as ( G ), and obtain the χ′ as ( G ) of some special graphs and present a conjecture: if G are graphs whose order of each component is at least six, then χ ′ as ( G ) ≤ Δ ( G ) + 2, where Δ( G ) is the maximum degree of G .
16465387
Rapid modeling of animated faces from video
Generating realistic 3D human face models and facial animations has been a persistent challenge in computer graphics. We have developed a system that constructs textured 3Dface models from videos with minimal user interaction. Our system takes images andvideo sequences of a face with an ordinary video camera. After five manual clicks ontwo images to tell the system where the eye corners, nose top and mouth corners are, thesystem automatically generates a realistic looking 3D human head model and the constructed model can be animated immediately. A user with a PC and an ordinary camera can use our system to generate his/her face model in a few minutes. Copyright © 2001 John Wiley & Sons, Ltd.