Multiple Object Tracking Using K-Shortest Paths Optimization

Multiple Object Tracking using Particle Swarm Optimization

This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multi...

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum c...

Geometric k Shortest Paths

We consider the problem of computing k shortest paths in a two-dimensional environment with polygonal obstacles, where the jth path, for 1  j  k, is the shortest path in the free space that is also homotopically distinct from each of the first j 1 paths. In fact, we consider a more general problem: given a source point s, construct a partition of the free space, called the kth shortest path m...

Near-shortest and K-shortest simple paths

We describe a new algorithm for solving the problem of enumerating all nearshortest simple (loopless) s-t paths in a graph G = (V,E) with non-negative edge lengths. Letting n = |V | and m = |E|, the time per path enumerated is O(nS(n,m)) given a user-selected shortest-path subroutine with complexity O(S(n,m)). When coupled with binary search, this algorithm solves the corresponding K-shortest s...

Time - Varying K Shortest Paths