OpenRaiser/Intern-Atlas huggingface dataset:
Non-rigid heart wall motion using MR tagging
Authors: Alistair A. Young, Leon Axel
Venue: CVPR
Year: 1992

A measure of deformation energy suitable for fitting deformable models to image data is described. An object's displacement is constrained to be globally smooth by penalizing the variation of the deformation gradient tensor. This homogeneous deformation measure is invariant to arbitrary rigid body motion of object and viewpoint, given the correspondence between model and data. It remains quadratic in the displacement parameters, leading to linear-least-squares fits. The method was used to reconstruct the nonhomogeneous 3-D motion of the heart wall from tomographic magnetic resonance images. A finite-element model of the left ventricle was deformed to fit material points tracked in biplanar views. Only the in-plane components were available from each separate image, the through-plane components being reconstructed in the fit.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Kinematic calibration of an active camera system
Authors: Gin-Shu Young, Tsai-Hong Hong, Martin Herman, Jackson C. S. Yang
Venue: CVPR
Year: 1992

A technique for the calibration of an active camera system is presented. The calibration of manipulator, camera-to-manipulator, camera, and base-to-world is treated in a unified and elegant way. In this approach, the camera frames and manipulator link frames are all related to the world frame, therefore the camera-to-manipulator and base-to-world calibration is very straightforward. The approach is simple, since it uses the form of one equation solving one parameter. Two experiments that verify the accuracy of the technique are reported.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Range image segmentation and fitting by residual consensus
Authors: Xinming Yu, Tien D. Bui, Adam Krzyzak
Venue: CVPR
Year: 1992

The authors randomly sample appropriate range image points and solve equations determined by these points for the parameters of selected primitive type. From K samples they measure residual consensus to choose one set of sample points that determines an equation having the best fit for the largest homogeneous surface patch in the current processing region. The residual consensus is measured by a compressed histogram method that works at various noise levels. The estimated surface patch is extracted out of the processing region to avoid further computation. A genetic algorithm is used to accelerate the search speed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Verifying and combining different visual cues into a 3-D model
Authors: Jiang Yu Zheng, Fumio Kishino
Venue: CVPR
Year: 1992

The authors attempt to combine results from different vision cues such as contour, motion and shading in an image sequence to obtain as complete a 3-D model as possible. Two problems must be solved. First, different features may appear to be the same image data. They should be classified so that different methods can be applied precisely. Second, output from different approaches may supplement, or overlap, each other. They should be qualified and then combined correctly and effectively. These issues are addressed by analyzing an image sequence taken when objects rotate around an axis. The features are verified according to their behaviour in the continuous images. Unknown areas and areas with single or multiple measurements are located. A strategy for combining these data is given.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Morphological structuring function decomposition
Authors: Xinhua Zhuang
Venue: CVPR
Year: 1992

The author attempts to solve the structuring function decomposition problem where the structuring function refers to the gray scale structuring element. A morphologically realizable representation for the structuring function that reduces the structuring function decomposition into a series of binary structuring element decompositions is presented. Recursive algorithms that are pipelinable for efficiently performing gray scale morphological operations are developed on the basis of proposed representation and decomposition. The results are beneficial to real-time image analysis in terms of computer architecture and software development.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Scaling images and image features via the renormalization group
Authors: Davi Geiger, João E. Kogler
Venue: CVPR
Year: 1993

The problem of obtaining high-quality images and image features at different scales is discussed. Emphasis is placed on a Markov image model described in a lattice by a Gaussian noise and a local regularization term depending upon the image discontinuities. An approximate self-similar property of the model is derived by a process of averaging over half of the lattice sites. This is known as the renormalization group approach. Two multiscale pyramid structures, one of images and the other of image discontinuities, are obtained. The coarse images generated by the proposed method are smooth and show good contrast. The approach, when applied in the reverse order, is capable of enlarging images, while accounting for the original image features. The quality of the derived pyramid is demonstrated by using it to help solve a segmentation problem.<<ETX>>
Detecting activities
Authors: Ramprasad Polana, Randal C. Nelson
Venue: CVPR
Year: 1993

A method of activity detection is described. This technique uses a periodicity measure on gray-level signals extracted along spatio-temporal reference curves. The technique is illustrated using real-world examples of activities. It is shown that the technique robustly detects complex periodic activities, while excluding nonperiodic motion. A technique to recognize these activities using the detection scheme described is proposed. It is not clear how much the periodicity alone is useful for recognition, but the authors believe that the phase information is valuable for activity recognition.<<ETX>>
An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization
Authors: W. Eric L. Grimson, Tomás Lozano-Pérez, Steve J. White, William M. Wells III, Ron Kikinis, Gil J. Ettinger
Venue: CVPR
Year: 1994

There is a need for frameless guidance systems to help neurosurgeons to plan the exact location of a craniotomy, to define the margins of tumors and to precisely identify locations of neighboring critical structures. We have developed an automatic technique for registering clinical data, such as segmented MRI or CT reconstructions, with the patient's head on the operating table. A second method calibrates the position of a video camera relative to the patient. The combination allows a visual mix of live video of the patient with the segmented 3D MRI or CT model, enabling enhanced reality techniques for planning and guiding neurosurgical procedures, and to interactively view extracranial or intracranial structures non-intrusively. Extensions of the method include image guided biopsies, focused therapeutic procedures and clinical studies involving change detection over time sequences of images.<<ETX>>
HOT curves for modelling and recognition of smooth curved 3D objects
Authors: Tanuja Joshi, Jean Ponce, B. Vijayakumar, David J. Kriegman
Venue: CVPR
Year: 1994

Arbitrary smooth curved 3D shapes are represented by a discrete set of high-order tangent (HOT) curves, where a surface admits HOTs. These curves determine the structure of the image contours and its catastrophic changes, and there is a natural correspondence between some of them and monocular contour features such as inflections and bitangents. We present a method for automatically constructing the HOT curves from continuous sequences of video images and describe an approach to object recognition using viewpoint-dependent monocular image features as indices into a database of models and as a basis for pose estimation. We have implemented both of the methods, and present results obtained from real images.<<ETX>>
Determination of motion parameters and estimation of point correspondences in small nonrigid deformations
Authors: Chandra Kambhamettu, Dmitry B. Goldgof, Matthew He
Venue: CVPR
Year: 1994

Recovery of motion parameters and point correspondences is a fundamental problem in computer vision. Although a great deal of research has been done in solving rigid motion, nonrigid motion analysis has only recently been addressed and is gaining interest due to its wide range of applications. This paper introduces a novel method for estimating motion parameters and point correspondences between surfaces under small nonrigid deformations. It uses the changes in differential geometric properties of surface under motion. Simulations are performed by generating nonrigid motion on an ellipsoidal data to illustrate performance and accuracy of derived algorithms, Then, the algorithm is tested on the sequence of facial range images. The motion parameters generated by the algorithm has also been used do detect the abnormality in cardiac images.<<ETX>>
Geometric heat equation and nonlinear diffusion of shapes and images
Authors: Benjamin B. Kimia, Kaleem Siddiqi
Venue: CVPR
Year: 1994

We propose a geometric smoothing method based on local curvature in shapes and images which is governed by the geometric heat equation and is a special case of the reaction-diffusion framework proposed by Faugeras (1990). For shapes, the approach is analogous to the classical heat equation smoothing, but with a renormalization by arc-length at each infinitesimal step. For images, the smoothing is similar to anisotropic diffusion in that, since the component of diffusion in the direction of the brightness gradient is nil, edge location and sharpness are left intact. We present several properties of curvature deformation smoothing of shape: it preserves inclusion order, annihilates extrema and inflection points without creating new ones, decreases total curvature, satisfies the semi-group property allowing for local iterative computations, etc. Curvature deformation smoothing of an image is based on viewing it as a collection of iso-intensity level sets, each of which is smoothed by curvature and then reassembled. This is shown to be mathematically sound and applicable to medical, aerial and range images.<<ETX>>
Active Face Tracking and Pose Estimation in an Interactive Room
Authors: Trevor Darrell, Baback Moghaddam, Alex Pentland
Venue: CVPR
Year: 1996

We demonstrate real-time face tracking and pose estimation in an unconstrained office environment with an active foveated camera. Using vision routines previously implemented for an interactive environment, we determine the spatial location of a user's head and guide an active camera to obtain foveated images of the face. Faces are analyzed using a set of eigenspaces indexed over both pose and world location. Closed loop feedback from the estimated facial location is used to guide the camera when a face is present in the foveated view. Our system can detect the head pose of an unconstrained user in real-time as he or she moves about an open room.
Convexity Analysis of Active Contour Problems
Authors: Christos Davatzikos, Jerry L. Prince
Venue: CVPR
Year: 1996

A general active contour formulation is considered and a convexity analysis of its energy function is presented. Conditions under which this formulation has a unique solution are derived; these conditions involve both the active contour energy potential and the regularization parameters. This analysis is then applied to four particular active contour formulations, revealing important characteristics of their convexity, and suggesting that external potentials involving center of mass computations may be better behaved than the usual potentials based on image gradients. Most importantly, our analysis provides an explanation for the poor convergence behavior at concave boundaries and suggests an alternate algorithm for approaching these types of boundaries.
Visual Organization for Figure/Ground Separation
Authors: Davi Geiger, Krishnan Kumaran, Laxmi Parida
Venue: CVPR
Year: 1996

A common factor in all illusory contour figures is the perception of a surface occluding part of a background. In our previous work, we have shown we could diffuse a proper set of junction hypothesis (what is salient or background) to obtain a surface where their boundaries represented illusory contours. Amodal completions emerge at the overlapping surfaces. We address the problem of selecting the best image organization (set of hypothesis). We propose an optimization criteria based on a coherence measure between pairs of junctions (correlation between the diffusion of each pair). A statistical physics approach to select the best organization is applied. The experiments suggest that despite the large number of possible organizations our approach may take only a few steps (in organization space) to select the best one.
Recovering the viewing parameters of random, translated and noisy projections of asymmetric objects
Authors: Peter D. Lauren, N. Nandhakumar
Venue: CVPR
Year: 1996

A method is described for the determination of the viewing parameters of randomly acquired projections of asymmetric objects. It extends upon the common lines algorithm by determining the relative orientation of projections from the location of lines of intersection among the Fourier transforms of the projections in three-dimensional Fourier space. A new technique for finding the lines of intersection in the presence of translational displacement, and for subsequently finding the translational displacement, is presented. A new technique for dealing with noise is also presented. The complete algorithm is described and its efficacy is demonstrated using real data. This technique may be applied to the three-dimensional reconstruction of viruses, molecules, and cells from in vivo images. It also has many other applications including the reconstruction of underwater scenes, radioastronomy, geoseismic analysis, and portable radiography for medical diagnosis and industrial inspection.
New, faster, more controlled fitting of implicit polynomial 2D curves and 3D surfaces to data
Authors: Zhibin Lei, David B. Cooper
Venue: CVPR
Year: 1996

Denote a point in the plane by z=(z,y) and a polynomial of nth degree in z by f(z) /spl Sigma//sub i,j//spl ges/o/sub 1/i+j/spl les/n(a/sub ij/x/sup i/y/sup j/). Denote by Z(f) the set of points for which f(z)=0. Z(f) is the 2D curve represented by f(z). In this paper, we present a new approach to fitting 2D curves to data in the plane (or 3D surfaces to range data) which has significant advantages over presently known methods. It requires considerably less computation and the resulting curve can be forced to lie close to the data set at prescribed points provided that there is an nth degree polynomial that can reasonably approximate the data. Linear programming is used to do the fitting. The approach can incorporate a variety of distance measures and global geometric constraints.
Dealing with occlusions in the eigenspace approach
Authors: Ales Leonardis, Horst Bischof
Venue: CVPR
Year: 1996

The basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. In this paper we present a new approach which successfully solves these problems. The major novelty of our approach lies in the way how the coefficients of the eigenimages are determined. Instead of computing the coefficients by a projection of the data onto the eigenimages, we extract them by a hypothesize-and-test paradigm using subsets of image points. Competing hypotheses are then subject to a selection procedure based on the Minimum Description Length principle. The approach enables us not only to reject outliers and to deal with occlusions but also to simultaneously use multiple classes of eigenimages.
Edge Detection and Ridge Detection with Automatic Scale Selection
Authors: Tony Lindeberg
Venue: CVPR
Year: 1996

When extracting features from image data, the type of information that can be extracted may be strongly dependent on the scales at which the feature detectors are applied. This article presents a systematic methodology for addressing this problem. A mechanism is presented for automatic selection of scale levels when detecting one-dimensional features, such as edges and ridges. A novel concept of a scale-space edge is introduced, defined as a connected set of points in scale-space at which: (i) the gradient magnitude assumes a local maximum in the gradient direction, and (ii) a normalized measure of the strength of the edge response is locally maximal over scales. An important property of this definition is that it allows the scale levels to vary along the edge. Two specific measures of edge strength are analysed in detail. It is shown that by expressing these in terms of /spl gamma/-normalized derivatives, an immediate consequence of this definition is that fine scales are selected for sharp edges (so as to reduce the shape distortions due to scale-space smoothing), whereas coarse scales are selected for diffuse edges, such that an edge model constitutes a valid abstraction of the intensity profile across the edge. With slight modifications, this idea can be used for formulating a ridge detector with automatic scale selection, having the characteristic property that the selected scales on a scale-space ridge instead reflect the width of the ridge.
Geometric and Photometric Constraints for Surface Recovery
Authors: Jiping Lu, Jim Little 0001
Venue: CVPR
Year: 1996

In this paper we present a novel approach to surface recovery from an image sequence of a rotating object. In this approach, the object is illuminated under a collinear light source (where the light source lies on or near the optical axis) and rotated on a controlled turntable. A wire-frame of 3D curves on the object surface is extracted by using shading and occluding contours in the image sequence. Then the whole object surface is recovered by interpolating the surface between curves on the wire-frame. The interpolation can be done by using geometric or photometric constraints. The photometric method uses shading information and is more powerful than geometric methods. The experimental results on real image sequence of matte and specular surfaces show that the technique is feasible and promising.
Texture Features and Learning Similarity
Authors: Wei-Ying Ma, B. S. Manjunath
Venue: CVPR
Year: 1996

This paper addresses two important issues related to texture pattern retrieval: feature extraction and similarity search. A Gabor feature representation for textured images is proposed, and its performance in pattern retrieval is evaluated on a large texture image database. These features compare favorably with other existing texture representations. A simple hybrid neural network algorithm is used to learn the similarity by simple clustering in the texture feature space. With learning similarity the performance of similar pattern retrieval improves significantly. An important aspect of this work is its application to real image data. Texture feature extraction with similarity learning is used to search through large aerial photographs. Feature clustering enables efficient search of the database as our experimental results indicate.
Viewpoint Variation in the Noise Sensitivity of Pose Estimation
Authors: Claus B. Madsen
Venue: CVPR
Year: 1996

The paper presents an analysis of the stability of pose estimation. The investigated pose estimation technique is based on orientations of three edge segments and provides the rotation part of object pose. The specific emphasis of the analysis is on determining how the stability varies with view point relative to an object. The stability investigation propagates the uncertainty in edge segment orientations to the resulting effect on the pose parameters. It is shown that there is a very strong variation in noise sensitivity over the range of viewpoints and that exactly what viewpoints offer highest robustness towards noise can be determined in advance. Experiments on real images verify the theoretical results and show that, dependent on viewpoint, pose parameter variance varies from 0.05 to 20 (degrees squared).
Controlled camera motions for scene reconstruction and exploration
Authors: Éric Marchand, François Chaumette
Venue: CVPR
Year: 1996

This paper deals with the 3D structure estimation and exploration of a scene using active vision. Our method is based on the structure from controlled motion approach which consists in constraining the camera motion in order to obtain a precise and robust estimation of the 3D structure of a geometrical primitive. Since this approach involves to gaze on the considered primitive, we present a method for connecting up many estimations in order to recover the complete spatial structure of scenes composed of cylinders and segments. We have developed perceptual strategies able to perform a succession of robust estimations without any assumption on the number and on the localization of the different objects. Furthermore, the proposed strategy ensures the completeness of the reconstruction. An exploration process centered on current visual features and on the structure of the previously studied primitives is presented. This leads to a gaze planning strategy that mainly uses a representation of known and unknown areas as a basis for selecting viewpoints. Finally, experiments carried out on a robotic cell have proved the validity of our approach.
Physics-Based Segmentation: Moving Beyond Color
Authors: Bruce A. Maxwell, Steven A. Shafer
Venue: CVPR
Year: 1996

We previously presented a framework for segmentation of complex scenes using multiple physical hypotheses for simple image regions. A consequence of that framework was a proposal for a new approach to the segmentation of complex scenes into regions corresponding to coherent surfaces rather than merely regions of similar color. Herein we present an implementation of this new approach and show example segmentations for scenes containing multi-colored piece-wise uniform objects. Using our approach we are able to intelligently segment scenes with objects of greater complexity than previous physics-based segmentation algorithms. The results show that by using general physical models we obtain segmentations that correspond more closely to coherent surfaces in the scene than segmentations found using only color.
Dense Nonrigid Motion Tracking from a Sequence of Velocity Fields
Authors: François G. Meyer, R. Todd Constable, Albert J. Sinusas, James S. Duncan
Venue: CVPR
Year: 1996

We have addressed the problem of tracking the non-rigid motion of the heart using a sequence of velocity fields and a sequence of contours. The information from both the contours and the dense velocity fields is integrated into a deforming mesh that is placed over the myocardium at one time frame and then tracked over the entire cardiac cycle. The deformation is guided by a smoothing filter that provides a compromise between (i) believing the dense field velocity and the contour data when it is crisp and coherent in a local spatial and temporal sense and (ii) employing a temporally smooth cyclic model of cardiac motion when contour and velocity data are not trustworthy. The method has been carefully evaluated with simulated data and phantom data. Experiments with in vivo data have also been conducted.