One of the most important goals of computer vision research is object recognition. Most current object recognition algorithms assume reliable image segmentation, which in practice is often not available. This research exploits the combination of the Hough method with the geometric hashing technique for model-based object recognition in seriously degraded intensity images. We describe the analys...

This paper proposes a segmentation-free, automatic and efficient procedure to detect general geometric quadric forms in point clouds, where clutter and occlusions are inevitable. Our everyday world is dominated by man-made objects which are designed using 3D primitives (such as planes, cones, spheres, cylinders, etc.). These objects are also omnipresent in industrial environments. This gives ri...

The concept of distance rationalizability of voting rules has been explored in recent years by several authors. Most previous work has dealt with a definition in terms of preference profiles. However, most voting rules in common use are anonymous and homogeneous. In this case there is a much more succinct representation (using the voting simplex) of the inputs to the rule. This representation h...

The automatic creation of geometric models from point clouds has numerous applications in CAD (e.g., reverse engineering, manufacturing, assembling) and, more general, shape modelling and processing. Given a segmented cloud representing man-made object, we propose method for recognizing simple primitives their interrelationships. Our approach is based on the Hough transform (HT) its ability to ...

In this paper we bring to bear some new tools from statistical learning on the analysis of roll call data. We present a new data-driven model for roll call voting that is geometric in nature. We construct the model by adapting the “Partition Decoupling Method,” an unsupervised learning technique originally developed for the analysis of families of time series, to produce a multiscale geometric ...

This paper presents a method to estimate and correct the positions of an indoor mobile robot. Scene matching is based on geometric hashing[9, 101. An optimization method[l2] of maximizing cross-correlation of image regions is used to estimation correction. We assume that the robot is equipped with two or more video cameras, a 2 0 laser range finder and an odometry system. The 3 0 CAD model of i...

We address the problem of 3D object recognition from a single 2D image using a model database. We develop a new method called enhanced geometric hashing. This approach allows us to solve for the indexing and the matching problem in one pass with linear complexity. Use of quasi-invariants allows us to index images in a new type of geometric hashing table. They include topological information of ...

Drawing on insights about the geometric structure of majority rule spatial voting games with Euclidean preferences derived from the Shapley– Owen value (Shapley and Owen, Int J Game Theory 18:339–356, 1989), we seek to explain why the outcomes of experimental committee majority rule spatial voting games are overwhelmingly located within the uncovered set (Bianco et al. We suggest that it is not...