Visual Quality Assessment of 3D/stereoscopic video (3D VQA) is significant for both quality monitoring and optimization of the existing 3D video services. In this paper, we build a 3D video database based on the lates...
详细信息
ISBN:
(纸本)9781509003556
Visual Quality Assessment of 3D/stereoscopic video (3D VQA) is significant for both quality monitoring and optimization of the existing 3D video services. In this paper, we build a 3D video database based on the latest 3D-HEVC video coding standard, to investigate the relationship among video quality, depth quality, and overall quality of experience (QoE) of 3D/stereoscopic video. We also analyze the pivotal factors to the video and depth qualities. Moreover, we develop a No-Reference 3D-HEVC bitstream-level objective video quality assessment model, which utilizes the key features extracted from the 3D video bitstreams to assess the perceived quality of the stereoscopic video. The model is verified to be effective on our database as compared with widely used 2D Full-Reference quality metrics as well as a state-of-the-art 3D FR pixel-level video quality metric.
Content-aware image retargeting has attracted substantial research interests in the related research community. However, so far there is still no method can preserve important image contents and structure well without...
详细信息
ISBN:
(纸本)9781479999897
Content-aware image retargeting has attracted substantial research interests in the related research community. However, so far there is still no method can preserve important image contents and structure well without introducing deformation. To address this problem, we propose a Saliency & Structure Preserving Multi-operator (SSPM) method. SSPM classifies images into three categories utilizing SIFT density to improve performance of saliency preservation, helping to mitigate negative influence from center-bias property of most existing saliency detection models. SSPM also employs different principles to improve structure preservation performance, including Earth Mover's Distance (EMD) and Gray-Level Cooccurrence Matrix (GLCM) to get optimal operator sequences for smart content-aware image retargeting. SSPM method not only can well preserve salient contents and structure, but also can greatly improve deformation resilience. Experimental results demonstrated that our method outperforms state-of-art image retargeting methods.
In all of the existing block-based image and video coding standards, blocks are processed in the fixed scan order. Then in HEVC intra coding, intra prediction is always based on the top and/or left neighboring reconst...
详细信息
ISBN:
(纸本)9781509053179
In all of the existing block-based image and video coding standards, blocks are processed in the fixed scan order. Then in HEVC intra coding, intra prediction is always based on the top and/or left neighboring reconstructed pixels, which incurs less accurate prediction for blocks where the spatial correlation is not along the topleft-to-bottomright direction. To obtain better intra prediction, we propose to flexibly determine the coding order of blocks in HEVC intra coding. Complying with the hierarchical quadtree structure in HEVC, our flexible block ordering (FBO) technique recursively decides the coding order of four sub-blocks when splitting one block. Moreover, we propose new methods to perform inter/extrapolation for intra prediction so as to fully utilize neighboring reconstructed pixels, not always being top/left. Experimental results show that our proposed FBO technique achieves on average 2.9% BD-rate reduction compared to HEVC baseline.
One largest problem for tracking-by-detection methods is the incomplete and noisy training set. Occlusion, illumination and many other problems could lead to this problem. Models that are not adaptive enough would fai...
详细信息
ISBN:
(纸本)9781467389600
One largest problem for tracking-by-detection methods is the incomplete and noisy training set. Occlusion, illumination and many other problems could lead to this problem. Models that are not adaptive enough would fail to track the target when drastic appearance change takes place. Adaptive ones, although keep tracking at first, could lose the target because of learning too many incorrect samples. In this paper, we present an ensemble model of random classifiers updated on different dataset. When the appearance of the target changes drastically and some sub-models are confused, the others could help correct the tracking result. A latent variable is added for choosing sub-models and it naturally leads to predicting the new samples with a weighted sum of sub-models. To calculate the weight, we add a generative model to each random classifier. Experiments show that our method could track the target robustly and accurately.
This paper addresses the issue on how to more effectively coordinate the depth with RGB aiming at boosting the performance of RGB-D object detection. Particularly, we investigate two primary ideas under the CNN model:...
详细信息
This paper addresses the issue on how to more effectively coordinate the depth with RGB aiming at boosting the performance of RGB-D object detection. Particularly, we investigate two primary ideas under the CNN model: property derivation and property fusion. Firstly, we propose that the depth can be utilized not only as a type of extra information besides RGB but also to derive more visual properties for comprehensively describing the objects of interest. So a two-stage learning framework consisting of property derivation and fusion is constructed. Here the properties can be derived either from the provided color/depth or their pairs (e.g. the geometry contour adopted in this paper). Secondly, we explore the fusion method of different properties in feature learning, which is boiled down to, under the CNN model, from which layer the properties should be fused together. The analysis shows that different semantic properties should be learned separately and combined before passing into the final classifier. Actually, such a detection way is in accordance with the mechanism of the primary neural cortex (V1) in brain. We experimentally evaluate the proposed method on the challenging dataset, and have achieved state-of-the-art performance.
The directional intra prediction (DIP) modes in HEVC are capable of predicting local continuous image features. Recently, intra block copy (IBC) is proposed for screen content coding, aiming at predicting non-local re...
详细信息
The directional intra prediction (DIP) modes in HEVC are capable of predicting local continuous image features. Recently, intra block copy (IBC) is proposed for screen content coding, aiming at predicting non-local recurrent image features. For natural video, we observe that recurrent features are often irregular and not aligned with blocks. Thus, we propose a combination of DIP and IBC with block partition for better intra prediction, where one block can be divided into several partitions, each of which may choose between DIP and IBC. We study an intra prediction scheme with the proposed combination, especially the rate-distortion optimization and entropy coding in the scheme. Preliminary experimental results show that the proposed combined intra prediction achieves as high as 5.8% bit-rate saving compared to HEVC anchor.
In this paper, we propose an improved robust model predictive control method for uncertain polytopic systems with input saturation constraints. For the synthesis of the robust controllers, a sequence of feedback contr...
详细信息
ISBN:
(纸本)9781467374439
In this paper, we propose an improved robust model predictive control method for uncertain polytopic systems with input saturation constraints. For the synthesis of the robust controllers, a sequence of feedback control laws and a parameterdependent Lyapunov function are utilized to further reduce the conservativeness and improve control performance. The state feedback control law is obtained by the solution of the convex optimization problem involving linear matrix inequalities(LMI)at each time step. The effectiveness of the proposed algorithm is demonstrated by a numerical example.
Tunnel boring machine(TBM) is widely used in long deep tunnel construction with its advantages of high efficiency, safety and low manpower. Cutterhead driving system provides power for excavating rocks and is an impor...
详细信息
ISBN:
(纸本)9781467374439
Tunnel boring machine(TBM) is widely used in long deep tunnel construction with its advantages of high efficiency, safety and low manpower. Cutterhead driving system provides power for excavating rocks and is an important component of TBM. Since the cutterhead system is driven by multiple induction motors, the synchronization control of multi-motor is critical important for high efficient excavating. The driving motors have to bear different excavating loads due to the uneven distribution of soils acting on the cutterhead surface. In this paper, all the driving motors are divided into two regions and a regional coupling based synchronization control strategy is proposed for the TBM cutterhead system. The dynamical induction motor model for vector control is established through coordinate transformation. The synchronous control of motors in each region is achieved by designing a master-slave motor control strategy. To deal with the torque difference between two regions, a fuzzy logic PID coordination controller is proposed for the master motors. Then, the synchronous control of driving motors is achieved by the presented regional coupling control strategy. The proposed synchronization control strategy is validated by simulating on multi-motor driving TBM cutterhead system for constant load torque and varying load torques, respectively. Compared with the single master-slave control, the proposed regional coupling control can achieve quicker dynamic response and better synchronization performance.
Leader-follower consensus is addressed in this paper for multi-agent systems with Lipschitz-type node dynamics and jointly connected dynamical topology. The main contribution of this works is to solve the leader-follo...
详细信息
ISBN:
(纸本)9781467374439
Leader-follower consensus is addressed in this paper for multi-agent systems with Lipschitz-type node dynamics and jointly connected dynamical topology. The main contribution of this works is to solve the leader-follower consensus problem with the general assumption that the network topology is specifically given and connected being removed. By considering the underlying communication graph for dynamic interaction topology, a bounded condition of consensus speed is proposed. By considering a combination of state information of follower and leader agents, a class of leader-follower consensus protocol is designed with the appropriate consensus speed. By appropriately constructing Lyapunov function, it is proved that the leader-follower consensus for the closed-loop multi-agent systems with Lipschitz-Type node dynamics and jointly connected dynamical topology can be achieved with carefully selected feedback gain matrix. Finally, one simulation example is presented to verify the proposed approach and demonstrate its effectiveness.
作者:
XU LiangYUAN JingqiDepartment of Automation
Shanghai Jiao Tong Universityand the Key Laboratory of System Control and Information ProcessingMinistry of Education of China
Dynamic modeling of the utility boiler is the basis of operation optimization of the coal-fired power plant. In this paper, the boiler-side whole process dynamic models of the subcritical coal-fired unit are establish...
详细信息
ISBN:
(纸本)9781467374439
Dynamic modeling of the utility boiler is the basis of operation optimization of the coal-fired power plant. In this paper, the boiler-side whole process dynamic models of the subcritical coal-fired unit are established based on the dynamic mass and energy balance. The models cover the important heat transfer facilities on the boiler side, including the evaporation system, superheaters, reheaters, and economizer. The energy storage or release in the metal wall of these facilities and all the heat losses are also considered in the models. At last, the pseudo-online simulation based on presented models is carried out with the history data captured by the distribution controlsystem of a real coal-fired power plant. It is found that model-based calculated total input energy is in good agreement with the offline assay value, which suggests the effectiveness of the presented models. The models have the potential for online process monitoring and operation optimization of the unit.
暂无评论