In this paper we propose an novel algorithm for detecting changes in street scenes when the vehicle revisits sections of the street at different times. The proposed algorithm detects structural geometric changes, changes due to dynamically moving objects and as well as changes in the street appearance (e.g. posters put up) between two traversal times. We exploit geometric, appearance and semant...

Markov networks utilize nonembedded probabilistic conditional independencies in order to provide an economical representation of a joint distribution in uncertainty management. In this paper we study several properties of nonembedded conditional independencies and show that they are in fact equivalent. The results presented here not only show the useful characteristics of an important subclass ...

Human perception of image distortions has been widely explored in recent years, however, research has not dealt with distortions due to geometric operations. As a consequence, there is a lack of objective visual quality measures for this class of distortions. In this paper we propose a method of objectively assessing the perceptual quality of geometrically distorted images. Our approach is base...

An efficient estimator for the expectation R f dP is constructed, where P is a Gibbs random field, and f is a local statistic, i. e. a functional depending on a finite number of coordinates. The estimator coincides with the empirical estimator under the conditions stated in Greenwood and Wefelmeyer [6], and covers the known special cases, namely the von Mises statistic for the i.i.d. underlying...

We address the problem of constructing and identifying a valid joint probability density function from a set of specified conditional densities. The approach taken is based on the development of relations between the joint and the conditional densities using Markov random fields (MRFs). We give a necessary and sufficient condition on the support sets of the random variables to allow these relat...

In this paper, we propose a new method for automatic extraction of breast mass spicules in 2-D mammography. Spicules are abnormal curvilinear structures which characterize most of malignant breast masses. They are important features for discrimination between benign and malignant masses. In our method, the curvilinear structures are first approximated by line segments derived from localized Rad...

We investigate the Bunimovich stadium dynamics and nd that in the limit of innnitely long stadium the symbolic dynamics is a subshift of nite type. For a stadium of nite length the Markov partitions are innnite, but the inadmissible symbol sequences can be determined exactly by means of the appropriate pruning front. We outline a construction of a sequence of nite Markov graph approximations by...

COMBINATORIAL MARKOV RANDOM FIELDS AND THEIR APPLICATIONS TO INFORMATION ORGANIZATION

Abstract How to establish the matching (or corresponding) between two different 3D shapes is a classical problem. This paper focused on the research on shape mapping of 3D mesh models, and proposed a shape mapping algorithm based on Hidden Markov Random Field and EM algorithm, as introducing a hidden state random variable associated with the adjacent blocks of shape matching when establishing H...

We present a discriminative method to classify data that have interdependencies in 2-D lattice. Although both Markov Random Fields (MRFs) and Conditional Random Fields (CRFs) are well-known methods for modeling such dependencies, they are often ineffective and inefficient, respectively. This is because many of the simplifying assumptions that underlie the MRF’s efficiency compromise its accurac...