A large number of landmarks selection techniques has been proposed. However, finding optimal solutions requires to solve some hard problems. In this paper, we consider the P- minimum overlapping region decomposition p...
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A large number of landmarks selection techniques has been proposed. However, finding optimal solutions requires to solve some hard problems. In this paper, we consider the P- minimum overlapping region decomposition problem that was proposed for landmarks selection. This problem is NP-complete. We describe an approach to solve the problem optimally. This approach is based on an explicit reduction from the problem to the satisfiability problem. Also, we consider some greedy algorithms for solution of the problem.
作者:
Gorbenko, AnnaUral Federal University
Department of Intelligent Systems Robotics of Mathematics and Computer Science Institute 620083 Ekaterinburg Russia
The problem of the longest common subsequence is a classical distance measure for strings. There have been several attempts to accommodate longest common subsequences along with some other distance measures. There are...
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The problem of the longest common subsequence is a classical distance measure for strings. There have been several attempts to accommodate longest common subsequences along with some other distance measures. There are a large number of different variants of the problem. In this paper, we consider the constrained longest common subsequence problem for two strings and arbitrary number of constraints. In particular, we consider an explicit reduction from the problem to the satisfiability problem and present experimental results for different satisfiability algorithms. It should be noted that different regularities in experimentally obtained data reveal important information about the underlying physical system. In this paper, we consider the problem of systematic monitoring of passenger flows. In particular, we use constrained longest common subsequences for tracking the image features.
A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. How...
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A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques.
作者:
Gorbenko, AnnaUral Federal University
Department of Intelligent Systems and Robotics of Mathematics and Computer Science Institute 620083 Ekaterinburg Russia
Different regularities can be used to identify the sequence among other sequences. Regularities allow us to infer an information about the evolution of the sequence. Tandem repeats are the most frequent in the genomes...
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Different regularities can be used to identify the sequence among other sequences. Regularities allow us to infer an information about the evolution of the sequence. Tandem repeats are the most frequent in the genomes of eukaryotes. Extraction of regularities is a widely studied problem. However, searching for exact tandem repeats can be too restrictive. So, a natural extension of the repetition is to allow errors. In this paper, we consider the approximate period problem. In particular, we consider an explicit reduction from the approximate period problem to the satisfiability problem and present experimental results for different satisfiability algorithms. Also, we consider the approximate period problem for sequences of motor primitives of robots. In particular, we use the approximate period problem to obtain some meta-parameters that adapt the global motion behavior. We try to use such metaparameters for learning to generalize motor primitives to a different behavior by trial and error without re-learning the task.
In this paper, we present a novel benchmark for the evaluation of RGB-D SLAM systems. We recorded a large set of image sequences from a Microsoft Kinect with highly accurate and time-synchronized ground truth camera p...
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ISBN:
(纸本)9781467317375
In this paper, we present a novel benchmark for the evaluation of RGB-D SLAM systems. We recorded a large set of image sequences from a Microsoft Kinect with highly accurate and time-synchronized ground truth camera poses from a motion capture system. The sequences contain both the color and depth images in full sensor resolution (640 × 480) at video frame rate (30 Hz). The ground-truth trajectory was obtained from a motion-capture system with eight high-speed tracking cameras (100 Hz). The dataset consists of 39 sequences that were recorded in an office environment and an industrial hall. The dataset covers a large variety of scenes and camera motions. We provide sequences for debugging with slow motions as well as longer trajectories with and without loop closures. Most sequences were recorded from a handheld Kinect with unconstrained 6-DOF motions but we also provide sequences from a Kinect mounted on a Pioneer 3 robot that was manually navigated through a cluttered indoor environment. To stimulate the comparison of different approaches, we provide automatic evaluation tools both for the evaluation of drift of visual odometry systems and the global pose error of SLAM systems. The benchmark website [1] contains all data, detailed descriptions of the scenes, specifications of the data formats, sample code, and evaluation tools.
Visual servoing was introduced in robotics nearly 4 decades ago. However until now, there are still only a handful of known examples of application of this technique in addressing real word robotics problems such as d...
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ISBN:
(纸本)9781467364096
Visual servoing was introduced in robotics nearly 4 decades ago. However until now, there are still only a handful of known examples of application of this technique in addressing real word robotics problems such as disaster response, assistance for elderly or handicapped people, etc. As the world is moving towards the use of robotics to improve quality of life, it is time to assess the challenges involved in applying visual servoing to solve real world problems. This paper presents an overview of these challenges, by asking the question what are the missing components for practical visual servoing? and by providing practical possible solutions for these components. Illustration of these challenges and our current practical solutions are given using our 7-DoFs Barrett WAM Arm.
We propose an approach for dependence tree structure learning via copula. A nonparametric algorithm for copula estimation is presented. Then a Chow-Liu like method based on dependence measure via copula is proposed to...
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We propose an approach for dependence tree structure learning via copula. A nonparametric algorithm for copula estimation is presented. Then a Chow-Liu like method based on dependence measure via copula is proposed to estimate maximum spanning bivariate copula associated with bivariate dependence relations. The main advantage of the approach is that learning with empirical copula focuses on dependence relations among random variables, without the need to know the properties of individual variables as well as without the requirement to specify parametric family of entire underlying distribution for individual variables. Experiments on two real-application data sets show the effectiveness of the proposed method.
An important example of bilateral symmetry in nature is the approximate bilateral symmetry exhibited by humans. Detecting and measuring bilateral symmetry in medical images should provide benefits in a clinical enviro...
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An important example of bilateral symmetry in nature is the approximate bilateral symmetry exhibited by humans. Detecting and measuring bilateral symmetry in medical images should provide benefits in a clinical environment. This paper presents a method for detecting the dominant plane of bilateral symmetry in an image of arbitrary dimension and subsequently measuring the degree of bilateral symmetry in the image. By adapting the work of others, we provide a unique solution to the problem by using a simple representation of the data and a more sensitive measure of symmetry.
The second international conference on Human-Robot Interaction (HRI-2007) was held in Arlington, Virginia, March 9-11, 2007. The theme of the conference was "Robot as Team Member" and included posters and pa...
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