Human action recognition technology has been applied to intelligent security surveillance, content-based image and video retrieval and natural user interface. How to make use of the new type of data, 3D skeleton joint...
Human action recognition technology has been applied to intelligent security surveillance, content-based image and video retrieval and natural user interface. How to make use of the new type of data, 3D skeleton joint position extracted by 3D depth camera, has been a highly active research topic. A posture representation model is proposed, which is invariant to limb length, length ratio between body parts and body orientation. This model contains polar angle and azimuthal angle of each limb in the spherical coordinate system which is established by the features of body joints. Hidden Markov Model（HMM） is exploited for recognition. Skeleton sequences of different body orientation are collected as experimental data. Experimental results demonstrate the effectiveness of our approach.
This paper presents a reliability assessment model for the wind power converter system (WPCS). In this study, the most influential factors of average wind speed and wind turbulence intensity are considered. First, WPC...
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ISBN:
(纸本)9781479957774
This paper presents a reliability assessment model for the wind power converter system (WPCS). In this study, the most influential factors of average wind speed and wind turbulence intensity are considered. First, WPCS operation state is partitioned into different phases in terms of different thermal stress levels which are determined by its operation conditions of average wind speed and wind turbulence intensity. Then, based on FIDES reliability guide, thermal factor and thermal cycling factor for each WPCS operation phases are calculated to indicate the contribution of average wind speed and wind turbulence to WPCS reliability. Finally, the randomly changed thermal profile is regulated by rain-flow cycling count algorithm and thus the junction temperature cycling information is extracted to calculate the thermal factor and thermal cycling factor. The reliability assessment on a real full-rated WPCS of a 2.5MW wind turbine with a permanentmagnet synchronous generator (PMSG) is carried out and the influences of cut-in, rated, cut-out wind speed and heat sink design parameters to the WPCS reliability is analyzed.
In this paper, T-G-P model is built to find maximum power point according to light intensity and temperature, making it easier and more clearly for photovoltaic system to track the MPP. A predictive controller conside...
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As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MP...
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As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MPC). The optimality is evaluated by comparing total performance of MPC with finite and infinite horizon optimal cost. Based on relaxed value iteration method, upper and lower bounds of optimality evaluation functions are expressed explicitly in terms of optimization horizon. These results reveal detailed characteristics on performance of closed-loop MPC systems due to using “receding horizon optimization” implementation style.
This paper concentrates on the optimal scheduling of electric vehicle(EV). The EV is scheduled for both operating stage and non-operating stage. With full consideration of operating income, regulation revenue and the ...
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This paper concentrates on the optimal scheduling of electric vehicle(EV). The EV is scheduled for both operating stage and non-operating stage. With full consideration of operating income, regulation revenue and the owner's habit, the cost minimization problem is formulated as a convex programming with coupling constrains. Dual decomposition is utilized to obtain the global optimal solution. Then, a modified online approach is introduced to alleviate the impact of price prediction error. The simulation reveals that our algorithms can reduce the cost to a large extent. Furthermore, it is demonstrated that the online scheduling scheme can achieve a similar performance compared with the optimal scheduling scheme having full knowledge of real time prices(RTP).
Interacting Multiple Model(IMM) filter faces significant outlier-caused *** this paper,the Bayesian probability update in IMM is found equivalent to Dempster's Rule of Combination which cannot handle evidence conf...
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ISBN:
(纸本)9781479900305
Interacting Multiple Model(IMM) filter faces significant outlier-caused *** this paper,the Bayesian probability update in IMM is found equivalent to Dempster's Rule of Combination which cannot handle evidence conflicts caused by ***,a novel robust MM(RMM) filter is proposed through introducing expert rules about mode evolvement and presenting the Likelihood Temporal Ratio(LTR) and building the Induced Combination Rule(ICR).Simulations about target tracking show the effectiveness of the proposed method.
This paper focuses on the load shifting problem in a household scenario with a large-capacity battery. We propose a novel Model Predictive control （MPC） framework to control the charge/discharge power of battery, he...
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ISBN:
(纸本)9781467355339
This paper focuses on the load shifting problem in a household scenario with a large-capacity battery. We propose a novel Model Predictive control （MPC） framework to control the charge/discharge power of battery, hence to shave the peak load. Being different from other studies, the framework is designed on the base of individual habit of energy consumption, as it is envisioned that the individual habit is critical for choosing the suitable energy services. In this paper, the habit is modeled as a Markov process and gradually learned by an iterative algorithm;thus, the habit can be utilized for the prediction of future energy consumption. Then, the rolling optimization is applied for the optimal control of the charge/discharge power of battery. It is shown by numerical simulations that the proposed approach can significantly reduce the peak load.
In this work, inspired from this biological motivation that in living cells, the execution time of different biological processes is difficult to know precisely and very sensitive to environmental factors that might b...
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3D reconstruction from multiple-view images has drawn a lot of attentions in computer graphics and computer vision communities. Traditional techniques usually end at discrete 3D point clouds computed from feature corr...
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3D reconstruction from multiple-view images has drawn a lot of attentions in computer graphics and computer vision communities. Traditional techniques usually end at discrete 3D point clouds computed from feature correspondence. However, geometric structure remains ambiguous in these unstructured point clouds, especially for man-made objects like buildings, indoor scenes. This paper proposes a new method to automatically reconstruct the main geometric structure of the scene composed of planar faces. First, dense 3D point clouds are reconstructed by applying patch-based multi-view stereo (PMVS) algorithm [1]. Then 3D planar primitives are extracted using a RANSAC-based approach [2]. We present a novel method to analyze the adjacency relations of the planar primitives to estimate the 3D intersection lines on the corresponding faces. Junctions and polygonal faces are computed from the 3D intersection lines along with complementary image information to compose the topology structure. Finally, texture for each face is extracted from the image under the best view. Experimental results demonstrate the feasibility of our system by successfully reconstructing the main structure of a wide range of scenes and constructing a texture-mapped piecewise-planar 3D model from images in multiple views.
In this paper, we propose a compressive tracking method via appearance model based on structural local patchs and improved Haar-like feature. In contrast to previous compressive tracking only considering the holistic ...
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In this paper, we propose a compressive tracking method via appearance model based on structural local patchs and improved Haar-like feature. In contrast to previous compressive tracking only considering the holistic representation, an object can be represented by local image patches with spatial layout in an object. This representation takes advantage of both partial information and spatial information of the target. Each local patch has a fixed position in the target field, and all local patches can represent the whole target. In addition, our appearance model based on features extracted from image patches, which can guarantee the randomness of the rectangular boxes and the distribution of the rectangular boxes over the entire image area, avoiding the randomness of the rectangular boxes is too strong to weak the feature expression. We sample the positive and negative samples and divide them into patchs to train a binary classification via a naive Bayes classifier with online update, then the classifier is used to discriminate the candidate samples. The candidate sample which gets the highest classify score is the target. After that we draw positive and negative samples in the same way with the candidate samples to update the classifier to get ready for next frame. Our approach helps not only locate the target more accurately but also can handle partial occlusion effectively. The proposed tracker is compared with several state-of-the-art trackers on some challenging video sequences. Our proposed tracker is better and more stable in both quantitative and qualitative comparisons.
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