In this paper, we proposed an architecture of a hierarchical networked urban traffic signal control system Based on Multi-agent. With mobile agent technology, traffic control strategies are designed as traffic control...
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In this paper, we proposed an architecture of a hierarchical networked urban traffic signal control system Based on Multi-agent. With mobile agent technology, traffic control strategies are designed as traffic control agents, which can move from device to device in a network. The system can reconfigure and replace these agents according to inconstant states of traffic environment and performances of agents. By this way, demand-based control is realized in traffic signal control system. Then we described the details and key technologies in the procession of agent-generation, agent-storage and agent-usage. At last, a prototype of the system is developed and basic functions of this system are tested by simulations. These simulations also confirm extensibility and effectiveness of the system.
In this paper, we propose a sparse coding algorithm based on matrix rank minimization and k-means clustering and for recognition. We consider the problem of removing the noise in the training samples and generating mo...
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ISBN:
(纸本)9781467314886
In this paper, we propose a sparse coding algorithm based on matrix rank minimization and k-means clustering and for recognition. We consider the problem of removing the noise in the training samples and generating more samples at the same time. To accomplish this, we extended the matrix rank minimization problem to cope with complex data. Samples from the same class are segmented into several groups by k-means clustering algorithm, and matrix rank minimization is applied on the clustered data to separate the noises and recover the low-rank structures in the grouped data. An over-complete dictionary is constructed by connecting the low-rank structures and the training samples together to keep the samples diversity. Sparse representation is operated based on this over-complete dictionary for recognition. Furthermore, a parameter is introduced to adjust the weighting of the coefficients that code the noises. We apply the proposed algorithm for character and face recognition. Experiments with improved performances validate the effectiveness of the proposed algorithm.
Interactive image segmentation which needs the user to give certain hard constraints has shown promising performance for object segmentation. In this paper, we consider characters in text image as a special kind of ob...
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Interactive image segmentation which needs the user to give certain hard constraints has shown promising performance for object segmentation. In this paper, we consider characters in text image as a special kind of object, and propose an adaptive graph cut based text binarization method to segment text from background. The main contributions of the paper lie in: 1) in order to make the binarization local adaptive with uneven background, the text region image is firstly roughly split into several sub-images on which graph cut is applied, and 2) considering the unique characteristics of the text, we propose to automatically classify some pixels as text or background with high confidence, severed as hard constraints seeds for graph cut to extract text from background by spreading the seeds into the whole sub-image. The experimental results show that our approach could get better performance in both character extraction accuracy and recognition accuracy.
Detecting text in video or natural scene image is quite challenging due to the complex background, various fonts and illumination conditions. The preprocessing period, which suppresses the nontext areas so as to highl...
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Detecting text in video or natural scene image is quite challenging due to the complex background, various fonts and illumination conditions. The preprocessing period, which suppresses the nontext areas so as to highlight the text areas, is the basis for further text detection. In this paper, a novel graph-based background suppression method for scene text detection is proposed. Considering each pixel as a node in the graph, our approach incorporates pixel-level and context-level features into a graph. Various factors contribute to the unary and pair wise cost function which is optimized via max-flow/min-cut algorithm [16] to get a binary image whose nontext pixels are suppressed so that text pixels are highlighted. Furthermore, the proposed background suppression method could be easily combined with other detection methods to improve the performance. Experimental results on ICDAR 2011 competition dataset show promising performance.
This paper proposes three training strategies based on impedance control, including passive training, damping-active training and spring-active training, for a 3- DOF lower limb rehabilitation robot designed for patie...
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ISBN:
(纸本)9781424441198
This paper proposes three training strategies based on impedance control, including passive training, damping-active training and spring-active training, for a 3- DOF lower limb rehabilitation robot designed for patients with paraplegia or hemiplegia. controllers with similar structure are developed for these training strategies, consisting of dual closed loops, the outer impedance control loop and the inner position/ velocity control loop, known as position-based impedance control method. Simulation results verify that position-based impedance control approach is feasible to accomplish the training strategies.
An integrated design approach, namely, design for control (DFC), is further studied in this paper. Previous work on the DFC approach usually takes the proportional-derivative (PD) control algorithm. It is revealed in ...
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An integrated design approach, namely, design for control (DFC), is further studied in this paper. Previous work on the DFC approach usually takes the proportional-derivative (PD) control algorithm. It is revealed in a closed-chain five-bar machine case that the PD-based DFC approach can only obtain a desired performance in set-point control task rather than tracking control task. In order to improve the robustness of this mechatronic system in terms of change of tasks, this paper suggests to use a "PD plus robust term" control algorithm in the DFC approach. Theoretical analysis shows that a satisfactory performance can be achieved by the proposed DFC. And it is also shown that the gain in the robust term plays an important role in bridging design of control algorithm and design of machine body. The general design principle of machine body is to design parameters of machine body to minimize the lower bound of this robust gain. Finally, the effectiveness of the proposed approach is validated by simulations.
From the view of combination of stereo vision and robot control, an active stereo vision for object tracking and location system is built to work on flexible manufacturing system. A method based on local HSV image and...
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From the view of combination of stereo vision and robot control, an active stereo vision for object tracking and location system is built to work on flexible manufacturing system. A method based on local HSV image and shape of object to recognize object is used for robot tracking. After the color segment, use the knowledge of shape of objects to recognize objects. And a technique for camera calibration based on plane square is proposed. It only requires the camera to observe a square at two (or more) different unknown orientations. Use the result of object recognize and camera calibration the robot can position and track the object. At the last of the paper, the results of object tracking experiments prove that the method is correct.
For spectators and public transport demand during the 16th Asian Games and the first Asian Para Games held in Guangzhou in 2010, Aided Decision-Making System of Public Transportation management for Guangzhou Asian Gam...
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ISBN:
(纸本)9781467313988
For spectators and public transport demand during the 16th Asian Games and the first Asian Para Games held in Guangzhou in 2010, Aided Decision-Making System of Public Transportation management for Guangzhou Asian Games had been developed to support public transport management decision. It can help public transport managers to enhance the level of public transport management from experience-based formulation and manual implementation to scientific computation-based formulation and automatic implementation by intelligent systems, to guarantee the traffic demand effectively during the games, and to improve the management of public transportation significantly.
This paper considers the problem of multiobjective fuzzy control design for a class of nonlinear spatially distributed processes (SDPs) described by parabolic partial differential equations (PDEs), which arise natural...
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This paper considers the problem of multiobjective fuzzy control design for a class of nonlinear spatially distributed processes (SDPs) described by parabolic partial differential equations (PDEs), which arise naturally in the modeling of diffusion-convection-reaction processes in finite spatial domains. Initially, the modal decomposition technique is applied to the SDP to formulate it as an infinite-dimensional singular perturbation model of ordinary differential equations (ODEs). An approximate nonlinear ODE system that captures the slow dynamics of the SDP is thus derived by singular perturbations. Subsequently, the Takagi-Sugeno fuzzy model is employed to represent the finite-dimensional slow system, which is used as the basis for the control design. A linear matrix inequality (LMI) approach is then developed for the design of multiobjective fuzzy controllers such that the closed-loop SDP is exponentially stable, and L-2 an performance bound is provided under a prescribed H-infinity constraint of disturbance attenuation for the slow system. Furthermore, using the existing LMI optimization technique, a suboptimal fuzzy controller can be obtained in the sense of minimizing the L-2 performance bound. Finally, the proposed method is applied to the control of the temperature profile of a catalytic rod.
Computer vision and video analytics become increasingly important for intelligent transport systems (ITSs), and violation detection is one of the key points in ITSs. It is widely recognized that image based systems ar...
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Computer vision and video analytics become increasingly important for intelligent transport systems (ITSs), and violation detection is one of the key points in ITSs. It is widely recognized that image based systems are flexible and versatile for advanced traffic monitoring and enforcement applications. In the proposed method, we first locate the tails from the images captured by a stationary camera, and then SURF(Speeded Up Robust Features) feature points are extracted from these tail images. A matching based rough detection stage is taken place to identify the high risk tails which are seen as violations and the low risk tails which are omitted as regular vehicles. Finally, color and shape information are taken advantages of to accomplish violation detection in the undetermined vehicles in the previous stage. Experiments are conducted using real live video sequences captured from an urban cross road. Results show that our method can potentially have a good performance.
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