8 research outputs found
Collision Computation Of Moving Bodies
In this paper, an explicit mathematical representation of n-dimensional bodies moving in translation along general trajectories is derived. This representation is used to find out if two moving bodies are going to collide. An optimization problem is developed for finding the time and location of collision. We consider the special cases of linear and piecewise linear trajectories. The collision in this case can be obtained by solving a linear program or a sequence of linear programs, respectively. The problem of finding the collision time and location of several moving bodies is cast as an integer programming problem. A comprehensive simulation study shows that this approach requires much lesser computation time when compared with the current approach of finding the collision between all pairs of bodies
An Algorithm For Computing The Distance Between Two Circular Disks
This paper presents an algorithm for computing the distance between two circular disks in three-dimensional space. A Kurush-Kuhn-Tucker (KKT) approach is used to solve the problem. We show that when the optimal points are not both at the borders of disks, the solutions of the KKT equations can be obtained in closed-form. For the case where the points are at the circumferences, the problem has no analytical solutions [IBM J. Res. Develop. 34 (5) (1990)]. Instead, we propose for the latter case an iterative algorithm based on computing the distance between a fixed point and a circle. We also show that the point-circle distance problem is solvable in closed-form, and the convergence of the numerical algorithm is linear
An Algorithm For Computing The Distance Between Two Circular Disks
This paper presents an algorithm for computing the distance between two circular disks in three-dimensional space. A Kurush-Kuhn-Tucker (KKT) approach is used to solve the problem. We show that when the optimal points are not both at the borders of disks, the solutions of the KKT equations can be obtained in closed-form. For the case where the points are at the circumferences, the problem has no analytical solutions [IBM J. Res. Develop. 34 (5) (1990)]. Instead, we propose for the latter case an iterative algorithm based on computing the distance between a fixed point and a circle. We also show that the point-circle distance problem is solvable in closed-form, and the convergence of the numerical algorithm is linear
Collision Computation Of Moving Bodies
In this paper, an explicit mathematical representation of n-dimensional bodies moving in translation along general trajectories is derived. This representation is used to find out if two moving bodies are going to collide. An optimization problem is developed for finding the time and location of collision. We consider the special cases of linear and piecewise linear trajectories. The collision in this case can be obtained by solving a linear program or a sequence of linear programs, respectively. The problem of finding the collision time and location of several moving bodies is cast as an integer programming problem. A comprehensive simulation study shows that this approach requires much lesser computation time when compared with the current approach of finding the collision between all pairs of bodies
Many-to-Many Graph Matching: a Continuous Relaxation Approach
Graphs provide an efficient tool for object representation in various
computer vision applications. Once graph-based representations are constructed,
an important question is how to compare graphs. This problem is often
formulated as a graph matching problem where one seeks a mapping between
vertices of two graphs which optimally aligns their structure. In the classical
formulation of graph matching, only one-to-one correspondences between vertices
are considered. However, in many applications, graphs cannot be matched
perfectly and it is more interesting to consider many-to-many correspondences
where clusters of vertices in one graph are matched to clusters of vertices in
the other graph. In this paper, we formulate the many-to-many graph matching
problem as a discrete optimization problem and propose an approximate algorithm
based on a continuous relaxation of the combinatorial problem. We compare our
method with other existing methods on several benchmark computer vision
datasets.Comment: 1