In this paper we propose a method to solve the stereo correspondence problem. The method matches features and feature relationships and can be paraphrased as follows. Linear edge segments are extracted from both the left and right images. Each such segment is characterized by its position and orientation in the image as well as its relationships with the nearby segments. A relational graph is t...

When trying to recover 3D structure from a set of images, the most di cult problem is establishing the correspondence between the measurements. Most existing approaches assume that features can be tracked across frames, whereas methods that exploit rigidity constraints to facilitate matching do so only under restricted camera motion. In this paper we propose a Bayesian approach that avoids the ...

We live in a dynamic environment in which objects change location over time. To maintain stable object representations the visual system must determine how newly sampled information relates to existing object representations, the correspondence problem. Spatiotemporal information is clearly an important factor that the visual system takes into account when solving the correspondence problem, bu...

Throughout the course of several years, significant progress has been made with regard to the accuracy and performance of pair-wise alignment techniques; however when considering low-resolution scans with minimal pairwise overlap, and scans with high levels of symmetry, the process of successfully performing sequential alignments in the object reconstruction process remains a challenging task. ...

Abstract. In this paper we present a new approach for establishing correspondences between sparse image features related by an unknown non-rigid mapping and corrupted by clutter and occlusion, such as points extracted from a pair of images containing a human figure in distinct poses. We formulate this matching task as an energy minimization problem by defining a complex objective function of th...

We present a new robust line matching algorithm for solving the model-to-image registration problem. Given a model consisting of 3D lines and a cluttered perspective image of this model, the algorithm simultaneously estimates the pose of the model and the correspondences of model lines to image lines. The algorithm combines softassign for determining correspondences and POSIT for determining po...

We describe a neural network able to rapidly establish correspondence between neural fields. The network is based on a cortical columnar model described earlier. It realizes dynamic links with the help of specialized columns that evaluate similarities between the activity distributions of local feature cell populations, are subject to a topology constraint, and gate the transfer of feature info...

Removing incorrect keypoint correspondences between two images is a fundamental yet challenging task in computer vision. A popular pipeline first computes feature vector for each correspondence and then trains binary classifier using these features. In this paper, we propose novel robust to better fulfill the above task. The basic observation that relative order of neighboring points around cor...

image analysis, feature correspondence, stereo, singular value, decomposition This paper presents a new simple method for achieving feature correspondence across a pair of images which requires no calibration information and draws from the method proposed by Scott and Longuet Higgins [8]. Despite the well-known combinatorial complexity of the problem, this work shows that an acceptably good sol...

In this paper we propose an efficient line feature-based 2D object recognition algorithm using a novel entropy correspondence measure (ECM) that encodes the probabilistic similarity between two line feature sets. Since the proposed ECM-based method uses the whole structural information of objects simultaneously for matching, it overcomes the common drawbacks of the conventional techniques that ...