This paper describes our preliminary development of a virtual robot teleoperation platform based on hand gesture recognition using visual information. Hand gestures in images captured by a camera are recognised to con...
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ISBN:
(纸本)9781479920747
This paper describes our preliminary development of a virtual robot teleoperation platform based on hand gesture recognition using visual information. Hand gestures in images captured by a camera are recognised to control a virtual iCub. We employ two methods to realise the classification: Adaptive Neuro-fuzzy Inference systems (ANFIS) and Support Vector Machines (SVM). We realise the teleoperation of a virtual robot using iCubSimulator. The technique in the paper will enable us to teleoperate a physical robot in the future work. In addition, a video server is set up to monitor the real robot. By using the parallel system we are able to improve the robot's performance. Based on the techniques presented in this paper, the virtual iCub can perform the specified actions remotely in a natural manner.
In this paper, a novel visual tracking algorithm that uses the target salient confidence (TSC) is proposed. Two contributions are summarized as follows. First, we put forward a novel target salient confidence (TSC) mo...
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ISBN:
(纸本)9781479958368
In this paper, a novel visual tracking algorithm that uses the target salient confidence (TSC) is proposed. Two contributions are summarized as follows. First, we put forward a novel target salient confidence (TSC) model which combines the static saliency map (SSM) based on the selective visual attention model, motion attention map (MAP) and the target prior confidence (TPC). Second, we propose to use the target salient confidence for particle filter. It manipulates the distribution expressed by the particle cloud towards a better match with the target salient confidence model. In this way particle sampling can be locked on those regions with higher target salient confidence. Experiments in some video sequences show that the target salient confidence is useful for visual tracking and our algorithm is effective.
Understanding the strategies to optimize/suppress information spreads under intense competition could provide important insights in a broad range of settings including viral marketing,emergency response and informatio...
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Understanding the strategies to optimize/suppress information spreads under intense competition could provide important insights in a broad range of settings including viral marketing,emergency response and information system ***,most of existing studies about competitive influence diffusion mainly focus on two-information competition *** date,the competitive influence maximization problem considering the mechanism of multi-information competition is still not well *** this paper,we conducted computational experiments to study the competitive influence maximization with multi-information competition *** applying an information diffusion model called limited attention model(LAM),we carried on two computational experiments to validate the model and investigate the relation between seed selection methods and the properties of information *** experimental results show that 1)the LAM model could reproduce the features of empirical distribution in Chinese social media;2)the eigenvector centrality-based heuristic is a reasonable seed selection method for competitive influence maximization *** results of this paper can provide significant potential implications for information system design and management.
In this paper, aiming at the indoor scene under monitoring by visual sensor network (VSN), an object recognition approach based on structural feature is presented. Firstly, we regard the output of existing line segmen...
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In this paper, aiming at the indoor scene under monitoring by visual sensor network (VSN), an object recognition approach based on structural feature is presented. Firstly, we regard the output of existing line segment detector LSD with proper parameters as the preliminary extraction result and it still will be further restored and split. Then, we give an inference model based on structural features of object including line segment ontology characteristics and relative relationship between the line segments. Finally, the objects are recognized with position information through inference. The effectiveness of the approach is verified, and the results show that our approach does not rely on segmentation and has robustness on partial defect and structural deformation to some extent.
Ground-based cloud classification is challenging due to extreme variations in the appearance of clouds under different atmospheric conditions. Texture classification techniques have recently been introduced to deal wi...
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Ground-based cloud classification is challenging due to extreme variations in the appearance of clouds under different atmospheric conditions. Texture classification techniques have recently been introduced to deal with this issue. A novel texture descriptor, the salient local binary pattern （SLBP）, is proposed for ground-based cloud classification. The SLBP takes advantage of the most frequently occurring patterns （the salient patterns） to capture descriptive information. This feature makes the SLBP robust to noise. Experimental results using ground-based cloud images demonstrate that the proposed method can achieve better results than current state-of-the-art methods.
According to the actual circumstance of the intersection,reasonably adjusting traffic light time can help to ease traffic pressure and save transportation *** this paper,Interval type-2 fuzzy sets and matched-degree a...
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According to the actual circumstance of the intersection,reasonably adjusting traffic light time can help to ease traffic pressure and save transportation *** this paper,Interval type-2 fuzzy sets and matched-degree are applied to the time of intersection signal adjusting,and five words are used to cover the range of adjusting lights’time,finally according to the average number of stranded vehicles,a query table is built to inquire and control the signal time during a certain period.
The leader-following output consensus problem of multi-agent systems (MAS) is studied in this paper. Each agent is modeled by a single-input single-output (SISO) system which can be further described by a controllable...
The leader-following output consensus problem of multi-agent systems (MAS) is studied in this paper. Each agent is modeled by a single-input single-output (SISO) system which can be further described by a controllable and observable linear state space model. An observer is constructed to estimate the agent's state, and the estimated state is shared with neighbor agents via the noisy communication channels. Similar to the previous work, in the proposed protocol a time-varying gain is employed to attenuate the noise's effect. However, in this paper, each agent is allowed to have its own time-varying gain. Some sufficient conditions on the time-varying gain are given for ensuring the consensus in the mean square sense. Finally, a simulation example is presented to verify the theoretical results.
Assessment and analysis of the intersection status can help to make the right choice of interventions,it’s can bring convenience to solve the traffic *** this paper,interval type-2 fuzzy sets is applied in the analys...
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Assessment and analysis of the intersection status can help to make the right choice of interventions,it’s can bring convenience to solve the traffic *** this paper,interval type-2 fuzzy sets is applied in the analysis of the intersection state and congestion intervention,dynamic fuzzy comprehensive evaluation and footprint of uncertainty are used to assess the intersection *** with the example of intersection congestion,through corresponding intervention measures to improve the intersections crowded *** the linguistic dynamic orbits of road status figured out.
Researches on office building energy consumption have been hot in these years, but few researchers consider the classification of office energy consumption performance which can evaluate user behaviors in order to off...
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Researches on office building energy consumption have been hot in these years, but few researchers consider the classification of office energy consumption performance which can evaluate user behaviors in order to offer a clear analysis of energy consumption and improve their energy saving consciousness. In this paper, we propose a novel hierarchical classification algorithm for evaluating energy consumption behaviors at a real energy management system, which combines fuzzy c-means clustering with GA (genetic algorithm)-based SVM (support vector machine) to fully utilize collected samples. The experiment results with real energy consumption data show that the proposed algorithm works well to distinguish the abnormal behaviors and classify energy consumption behaviors accurately on normal offices.
This paper introduces an approach to estimate the true states for stochastic Boolean dynamic system(SBDS), where the state evolution is governed by Boolean functions with additive binary process noise while the measur...
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This paper introduces an approach to estimate the true states for stochastic Boolean dynamic system(SBDS), where the state evolution is governed by Boolean functions with additive binary process noise while the measurement is an arbitrary function of the state yet with additive binary measurement *** problem of figuring out the true state using the only available noisy outputs is crucial for practical applications of Boolean dynamic system models, however, for such Boolean systems with wide background, there are no ready-to-use convenient tools like Kalman filter for linear systems. To resolve this challenging problem, an approach based on Bayesian filtering called Boolean Bayesian Filter(BBF) is put forward to estimate the true states of SBDS, and an efficient algorithm is presented for their exact computation. An index to evaluate the filtering performance,named estimation error rate, is put forward in this paper as well. In addition, extensive simulations via actual examples have illustrated the effectiveness of the proposed algorithm based on BBF.
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