1,625 research outputs found
Real-Time Salient Closed Boundary Tracking via Line Segments Perceptual Grouping
This paper presents a novel real-time method for tracking salient closed
boundaries from video image sequences. This method operates on a set of
straight line segments that are produced by line detection. The tracking scheme
is coherently integrated into a perceptual grouping framework in which the
visual tracking problem is tackled by identifying a subset of these line
segments and connecting them sequentially to form a closed boundary with the
largest saliency and a certain similarity to the previous one. Specifically, we
define a new tracking criterion which combines a grouping cost and an area
similarity constraint. The proposed criterion makes the resulting boundary
tracking more robust to local minima. To achieve real-time tracking
performance, we use Delaunay Triangulation to build a graph model with the
detected line segments and then reduce the tracking problem to finding the
optimal cycle in this graph. This is solved by our newly proposed closed
boundary candidates searching algorithm called "Bidirectional Shortest Path
(BDSP)". The efficiency and robustness of the proposed method are tested on
real video sequences as well as during a robot arm pouring experiment.Comment: 7 pages, 8 figures, The 2017 IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS 2017) submission ID 103
An Improved Algorithm for Finding the Shortest Synchronizing Words
A synchronizing word of a deterministic finite complete automaton is a word
whose action maps every state to a single one. Finding a shortest or a short
synchronizing word is a central computational problem in the theory of
synchronizing automata and is applied in other areas such as model-based
testing and the theory of codes. Because the problem of finding a shortest
synchronizing word is computationally hard, among \emph{exact} algorithms only
exponential ones are known. We redesign the previously fastest known exact
algorithm based on the bidirectional breadth-first search and improve it with
respect to time and space in a practical sense. We develop new algorithmic
enhancements and adapt the algorithm to multithreaded and GPU computing. Our
experiments show that the new algorithm is multiple times faster than the
previously fastest one and its advantage quickly grows with the hardness of the
problem instance. Given a modest time limit, we compute the lengths of the
shortest synchronizing words for random binary automata up to 570 states,
significantly beating the previous record. We refine the experimental
estimation of the average reset threshold of these automata. Finally, we
develop a general computational package devoted to the problem, where an
efficient and practical implementation of our algorithm is included, together
with several well-known heuristics.Comment: Full version of ESA 2022 pape
An Improved Algorithm for Finding the Shortest Synchronizing Words
A synchronizing word of a deterministic finite complete automaton is a word whose action maps every state to a single one. Finding a shortest or a short synchronizing word is a central computational problem in the theory of synchronizing automata and is applied in other areas such as model-based testing and the theory of codes. Because the problem of finding a shortest synchronizing word is computationally hard, among exact algorithms only exponential ones are known. We redesign the previously fastest known exact algorithm based on the bidirectional breadth-first search and improve it with respect to time and space in a practical sense. We develop new algorithmic enhancements and adapt the algorithm to multithreaded and GPU computing. Our experiments show that the new algorithm is multiple times faster than the previously fastest one and its advantage quickly grows with the hardness of the problem instance. Given a modest time limit, we compute the lengths of the shortest synchronizing words for random binary automata up to 570 states, significantly beating the previous record. We refine the experimental estimation of the average reset threshold of these automata. Finally, we develop a general computational package devoted to the problem, where an efficient and practical implementation of our algorithm is included, together with several well-known heuristics
Quickest Paths in Simulations of Pedestrians
This contribution proposes a method to make agents in a microscopic
simulation of pedestrian traffic walk approximately along a path of estimated
minimal remaining travel time to their destination. Usually models of
pedestrian dynamics are (implicitly) built on the assumption that pedestrians
walk along the shortest path. Model elements formulated to make pedestrians
locally avoid collisions and intrusion into personal space do not produce
motion on quickest paths. Therefore a special model element is needed, if one
wants to model and simulate pedestrians for whom travel time matters most (e.g.
travelers in a station hall who are late for a train). Here such a model
element is proposed, discussed and used within the Social Force Model.Comment: revised version submitte
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