15389117
A Framework for Automatic Landmark Identification Using a New Method of Nonrigid Correspondence
A framework for automatic landmark identification is presented based on an algorithm for corresponding the boundaries of two shapes. The auto-landmarking framework employs a binary tree of corresponded pairs of shapes to generate landmarks automatically on each of a set of example shapes. The landmarks are used to train statistical shape models, known as point distribution models. The correspondence algorithm locates a matching pair of sparse polygonal approximations, one for each of a pair of boundaries by minimizing a cost function, using a greedy algorithm. The cost function expresses the dissimilarity in both the shape and representation error (with respect to the defining boundary) of the sparse polygons. Results are presented for three classes of shape which exhibit various types of nonrigid deformation.
9944487
Constrained Active Appearance Models
Active Appearance Models (AAMs) have been shown to be useful for interpreting images of deformable objects. Here we place the AAM matching algorithm in a statistical framework, allowing extra constraints to be applied. This enables the models to be combined with other methods of object location. We demonstrate how user interaction can be used to guide the search and give results of experiments showing the effect of constraints on the performance of model matching.
117576
Transforming pixel signatures into an improved metric space
Abstract We address the problem of using scale-orientation pixel signatures to characterise local structure in X-ray mammograms, though the method we report is of general application. When signatures are treated as vectors for statistical analysis, the Euclidean metric is not well behaved. We have previously described a Best Partial Match (BPM) metric that measures signature similarity more naturally, but at high computational cost. We present a method for transforming signatures into a new space in which Euclidean distance approximates BPM distance, allowing BPM distance to be estimated at low computational cost. The new space is constructed using multi-dimensional scaling. The nonlinear transformation between the old and new spaces is learned using support vector regression. We present experimental results for mammographic data.
35191926
Automatic Extraction of the Face Identity-Subspace
Facial variation divides into a number of functional subspaces, and ensemblespecific variation. An improved method of measuring these is presented, within the space defined by an Appearance Model. Initial estimates of the subspaces (lighting, pose, identity and expression) are obtained by Principal Components Analysis on appropriate groups of faces. An expectationmaximization algorithm is applied to image codings to maximise the probability of coding across these non-orthogonal subspaces. Ensemble specific variation is then removed by measuring the spatial predictability of the eigenvectors excluding those which are less predictable than the ensemble. These procedures significantly enhance identity recognition for a disjoint test set.
18409496
Building optimal 2D statistical shape models
Statistical shape models are used widely as a basis for segmenting and interpreting images. A major drawback of the approach is the need, during training, to establish a dense correspondence across a training set of segmented shapes. We show that model construction can be treated as an optimisation problem, automating the process and guaranteeing the effectiveness of the resulting models. This is achieved by optimising an objective function with respect to the correspondence. We use an information theoretic objective function that directly promotes desirable features of the model. This is coupled with an effective method of manipulating correspondence, based on reparameterising each training shape, to build optimal statistical shape models. The method is evaluated on several training sets of shapes, showing that it constructs better models than alternative approaches. q 2003 Elsevier B.V. All rights reserved.
17273589
Developing a Measure of Similarity between Pixel Signatures
Our previous work in computer-aided mammography has used scaleorientation pixel signatures that provide a rich description of local structure. We describe work using the transportation (`earth mover') algorithm to de ne a measure of similarity between two signatures that recognises similar structures whilst remaining robust to background variability and the presence of other structures. Speci cally, we investigate an un-normalised, normalised and novel best-partialmatching (BPM) approach to measuring this transportation distance and compare it with Euclidean distance. Receiver operating characteristic (ROC) methodology is used to compare performance and an example of clinical application is given. The BPM approach outperforms the other methods.
16474707
Reconstructing Polyhedral Models of Architectural Scenes from Photographs
This paper presents a new image-based modeling method that facilitates the recovery of accurate polyhedral models of architectural scenes. The method is particularly effective because it exploits many of the constraints that are characteristic of architectural scenes. This work is placed in the context of the FaCade project, whose goal is to use images to produce photo-realistic novel views of architectural scenes.
2497525
Structure and Motion from Line Segments in Multiple Images
This paper presents a new method for recovering the three dimensional structure of a scene composed of straight line segments using the image data obtained from a moving camera. The recovery algorithm is formulated in terms of an objective function which measures the total squared distance in the image plane between the observed edge segments and the projections (perspective) of the reconstructed lines. This objective function is minimized with respect to the line parameters and the camera positions to obtain an estimate for the structure of the scene. The effectiveness of this approach is demonstrated quantitatively through extensive simulations and qualitatively with actual image sequences. The implementation is being made publicly available. >
3172134
VideoPlus: A Method for Capturing the Structure and Appearance of Immersive Environments
This paper describes an approach to capturing the appearance and structure of immersive environments based on the video imagery obtained with an omnidirectional camera system. The scheme proceeds by recovering the 3D positions of a set of point and line features in the world from image correspondences in a small set of key frames in the image sequence. Once the locations of these features have been recovered the position of the camera during every frame in the sequence can be determined by using these recovered features as fiducials and estimating camera pose based on the location of corresponding image features in each frame. The end result of the procedure is an omnidirectional video sequence where every frame is augmented with its pose with respect to an absolute reference frame and a 3D model of the environment composed of point and line features in the scene.By augmenting the video clip with pose information we provide the viewer with the ability to navigate the image sequence in new and interesting ways. More specifically the user can use the pose information to travel through the video sequence with a trajectory different from the one taken by the original camera operator. This freedom presents the end user with an opportunity to immerse themselves within a remote environment.
5491850
A comparative study of vision-based lateral control strategies for autonomous highway driving
This paper will present the results of a comparative study of a set of vision-based control strategies that have been applied to the problem of steering an autonomous vehicle along a highway. The aim of this work has been to further our understanding of the characteristics of various control laws that could be applied to this problem with a view to making informed design decisions. The control strategies that we explored include a lead lag control law, a full-state linear controller and input-output linearizing control law. Each of these control strategies was implemented and tested on our experimental vehicle, a Honda Accord LX, both with and without a curvature feedforward component.
110260194
A Comparative Study of Vision-Based Lateral Control Strategies for Autonomous Highway Driving
With the increasing speeds of modern microprocessors, it has become ever more common for computer-vision algorithms to find application in real-time control tasks. In this paper, we present an analysis of the problem of steering an autonomous vehicle along a highway based on the images obtained from a CCD camera mounted in the vehicle. We explore the effects of changing various important system parameters like the vehicle velocity, the look-ahead range of the vision sensor, and the processing delay associated with the perception and control systems. We also present the results of a series of experiments that were designed to provide a systematic comparison of a number of control strategies. The control strategies that were explored include a lead-lag control law, a full-state linear controller, and an input-output linearizing control law. Each of these control strategies was implemented and tested at highway speeds on our experimental vehicle platform, a Honda Accord LX sedan.