1,720,963 research outputs found
Windsurf: Region-based image retrieval using wavelets
No full textIn this paper we present WINDSURF (Wavelet-Based Indexing of Images Using Region Fragmentation), a new approach to content-based image retrieval. The method uses the wavelet transform to extract color and texture features from an image and applies a clustering technique to partition the image into a set of "homogeneous" regions. Similarity between images is assessed by using the Bhattacharyya distance to compare region descriptors, and then combining the results at image level. Experimental results on a testbed of 10,000 general-purpose images show that our approach is very effective in retrieving images that are "semantically" similar to the query image. In particular, we compared results of WINDSURF with the approach by Stricker and Orengo [11], showing that a significant improvement is obtained in the quality of the result
Efficient solution algorithms for the Bounded Acceleration Shortest Path problem
No full textThe purpose of this work is to introduce and characterize the Bounded Acceleration Shortest Path (BASP) problem, a generalization of the Shortest Path (SP) problem. This problem is associated to a graph: nodes represent positions of a mobile vehicle and arcs are associated to pre-assigned geometric paths that connect these positions. BASP consists in finding the minimum-time path between two nodes. Differently from SP, we require that the vehicle satisfy bounds on maximum and minimum acceleration and speed, that depend on the vehicle position on the currently traveled arc. We propose solution algorithms that achieves polynomial time-complexity under some additional hypotheses on problem data
Shortest path with acceleration constraints: complexity and approximation algorithms
Full text linkWe introduce a variant of the Shortest Path Problem (SPP), in which we impose additional constraints on the acceleration over the arcs, and call it Bounded Acceleration SPP (BASP). This variant is inspired by an industrial application: a vehicle needs to travel from its current position to a target one in minimum-time, following pre-defined geometric paths connecting positions within a facility, while satisfying some speed and acceleration constraints depending on the vehicle position along the currently traveled path. We characterize the complexity of BASP, proving its NP-hardness. We also show that, under additional hypotheses on problem data, the problem admits a pseudo-polynomial time-complexity algorithm. Moreover, we present an approximation algorithm with polynomial time-complexity with respect to the data of the original problem and the inverse of the approximation factor ε. Finally, we present some computational experiments to evaluate the performance of the proposed approximation algorithm
Local Optimization of MAPF Solutions on Directed Graphs
No full textAmong sub-optimal Multi-Agent Path Finding (MAPF) solvers, rule-based algorithms are particularly appealing since they are complete. Even in crowded scenarios, they allow finding a feasible solution that brings each agent to its target, preventing deadlock situations. However, generally, rule-based algorithms provide solutions that are much longer than the opti-malone. The main contribution of this paper is the introduction of an iterative local search procedure in MAPF. We start from a feasible suboptimal solution and we perform a local search in a neighborhood of this solution, to find a shorter one. Iteratively, we repeat this procedure until the solution cannot be shortened any longer. At the end, we obtain a solution, that is still sub-optimal, but, in general, of much better quality than the initial one. We use dynamic programming for the local search procedure. Under this respect, the fact that our search is local is fundamental to reduce the time complexity of the algorithm. Indeed, if we apply a standard dynamic programming the number of explored states grows exponentially with the number of agents. As we will see, the introduction of a locality constraint allows solving the (local) dynamic programming problem in a time that grows only polynomially with respect to the number of agents
Constrained Motion Planning and Multi-Agent Path Finding on directed graphs
Full text linkWe discuss C-MP and C-MAPF, generalizations of the classical Motion Planning (MP) and Multi-Agent Path Finding (MAPF) problems on a directed graph G. Namely, we enforce an upper bound on the number of agents that occupy each member of a family of vertex subsets. For instance, this constraint allows maintaining a safety distance between agents. We prove that finding a feasible solution of C-MP and C-MAPF is NP-hard. Also, we propose a method to convert these problems to standard MP and MAPF by strengthening the constraints. The method consists in finding a subset of vertices W and a reduced graph GW, such that a feasible solution of MP and MAPF on GW provides, in polynomial time, a feasible solution of C-MP and C-MAPF on G. However, since the conversion into standard MP and MAPF is obtained by strengthening constraints, feasible solutions of C-MP and C-MAPF on G may exist even if MP and MAPF on GW do not admit any feasible solution. We also study the problem of finding W of maximum cardinality. First, we show that such problem is strongly NP-hard. Then, we propose a heuristic approach for its solution
Identification of Cyclists' Route Choice Criteria
No full textThe behavior of cyclists when choosing the path to follow along a road network is not uniform. Some of them are mostly interested in minimizing the travelled distance, but some others may also take into account other features such as safety of the roads or level of pollution, including carbon dioxide emission by the cars or even the noise pollution. Identifying the different groups of users, estimating the numerical consistency of each of these groups, and reporting the weights assigned by each group to different characteristics of the road network, is quite relevant. Indeed, when decision makers need to assign some budget for infrastructural interventions, they need to know the impact of their decisions, and this is strictly related to the way users perceive different features of the road network. In this paper, we propose an optimization approach to detect the weights assigned to different road features by various user groups, leveraging knowledge of the true paths followed by them, accessible, for example, through data collected by bike-sharing services
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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