To improve free viewpoint video (FVV) coding efficiency and optimize the quality of the synthesized virtual view video, this paper proposes a depth-assisted FVV coding framework and analyzes the rate-distortion (R-D) property of the synthesized virtual view video in FVV coding. In the depth-assisted FVV coding framework, the depth assigned disparity compensated prediction is introduced to exploit the correlation between multiview video (MVV) and depth. To model the R-D property of the synthesized virtual view video, a region-based view synthesis distortion estimation approach is investigated with respect to the distortion of MVV and depth. Subsequently, the general R-D property estimation models of MVV and depth are analyzed. Finally, a rate-allocation scheme is designed to optimize the quantization parameter pair of MVV and depth in FVV coding. The simulation results demonstrate that the proposed depth-assisted FVV coding framework can improve the FVV coding efficiency. The region-based view synthesis distortion estimation approach and the general R-D model are able to precisely approximate the R-D property of synthesized virtual view video in the multiview video plus depth based FVV coding frameworks. The proposed rate-allocation scheme can optimize the overall FVV coding efficiency to achieve a high-quality reconstructed video at the desired viewpoint with a given rate constraint.

Recently, extensive research efforts have been dedicated to view-based methods for 3-D object retrieval due to the highly discriminative property of multiviews for 3-D object representation. However, most of state-of-the-art approaches highly depend on their own camera array settings for capturing views of 3-D objects. In order to move toward a general framework for 3-D object retrieval without the limitation of camera array restriction, a camera constraint-free view-based (CCFV) 3-D object retrieval algorithm is proposed in this paper. In this framework, each object is represented by a free set of views, which means that these views can be captured from any direction without camera constraint. For each query object, we first cluster all query views to generate the view clusters, which are then used to build the query models. For a more accurate 3-D object comparison, a positive matching model and a negative matching model are individually trained using positive and negative matched samples, respectively. The CCFV model is generated on the basis of the query Gaussian models by combining the positive matching model and the negative matching model. The CCFV removes the constraint of static camera array settings for view capturing and can be applied to any view-based 3-D object database. We conduct experiments on the National Taiwan University 3-D model database and the ETH 3-D object database. Experimental results show that the proposed scheme can achieve better performance than state-of-the-art methods.

The explosively increasing 3-D objects make their efficient retrieval technology highly desired. Extensive research efforts have been dedicated to view-based 3-D object retrieval for its advantage of using 2-D views to represent 3-D objects. In this paradigm, typically the retrieval is accomplished by matching the views of the query object with the objects in database. However, using all the query views may not only introduce difficulty in rapid retrieval but also degrade retrieval accuracy when there is a mismatch between the query views and the object views in the database. In this work, we propose an interactive 3-D object retrieval scheme. Given a set of query views, we first perform clustering to obtain several candidates. We then incrementally select query views for object matching: in each round of relevance feedback, we only add the query view that is judged to be the most informative one based on the labeling information. In addition, we also propose an efficient approach to learn a distance metric for the newly selected query view and the weights for combining all of the selected query views. We conduct experiments on the National Taiwan University 3D Model database, ETH 3D object collection, and Shape Retrieval Content of Non-Rigid 3D Model, and results demonstrated that our approach not only significantly speeds up the retrieval process but also achieves encouraging retrieval performance.

Summary form only given. In 3D video (3DV), the virtual view images are commonly synthesized by the color and depth images of the reference views with image based rendering (IBR). Thus, in 3DV coding, to provide the high-quality interactive viewpoint video to audience, it is necessary to jointly optimize coding efficiency of color and depth images at a given bit-rate by rate-distortion (R-D) property analysis of 3DV coding.to calculate Edw, a region based distortion model is proposed firstly. In IBR, depth quantization error will cause the disparities between the pixels of the virtual view and the correspondent pixels of the reference views changed.

The increasing number of available 3D objects makes their efficient retrieval technology highly desired. Extensive research has been dedicated to view-based 3D object retrieval because of its advantage of 2D views for 3D object content representation. In this paradigm, typically the retrieval is accomplished based a set of different views of the query object, and focuses on the 3D object representation, matching and indexing. In this work, we present another aspect towards 3D object retrieval: intelligent query. Intelligent query includes query selection, query description and combination, and assistive query. We will show how this scheme is ideally suit for the 3D object retrieval problem. We conduct experiments on the National Taiwan University 3D Model database and results demonstrated that our approach can improve retrieval performance. Finally, we give insight into the future of the intelligent query for 3D object retrieval.

In this paper, we propose a multi-bipartite graph reinforcement model for representative views re-ranking in 3D model retrieval. Given the views of one query 3D model, all query views are grouped into clusters to generate representative views and corresponding original weights. In the retrieval procedure, labeled positive retrieval results are employed to refine the query information. Each group of views from positive retrieval results and the group of representative query views are employed to construct a bipartite graph, and a multi-bipartite graph reinforcement algorithm is performed on these bipartite graphs to re-rank all views. Then the weights of all representative query views are updated. Experimental results on two 3D model databases are provided to justify the effectiveness of the proposed method.

View-based method becomes an essential approach to 3D object retrieval in recent years. In the view-based 3D object retrieval framework, each object is described by a set of views and representative features are extracted from these views to match the objects in database. In this paper, we propose a novel 3D multi-view representation method, Bag-of-Region-Words (BoRW). It first gridly selects points in each view and extracts local SIFT features. Each local feature is encoded into a visual word with a trained visual vocabulary. Then each view is split into several regions, and each region is represented by a bag-of-visual-words feature vector. All the obtained regions are further grouped into clusters based on the bag-of-visual-words feature, and one feature is selected from each cluster with corresponding weight. In this way, each object is described by a set of BoRW. The Earth Movers Distance is employed to estimate the distance between two BoRW feature vectors. Experimental results show that the proposed method can achieve better retrieval performance than existing methods.

In our previous work, we have realized virtual slope walking that a robot can walk on level ground as it walks down a virtual slope by leg length modulation. In this paper, we present the instantaneous leg extension model of virtual slope walking to analyze the essentials of virtual slope walking. It has two straight massless legs and a point mass body at the hip. The stance leg is extended instantaneously while the swing leg is swung and shortened actively. We demonstrate that this model can exhibit stable walking cycles on level ground. We obtain the sufficient conditions for the existence of the fixed point. We then illustrate the effect of the model parameters on the fixed point to show how the fixed point can be determined by adjusting the parameters. Further, we theoretically proved that the fixed point is asymptotically stable, meaning that it is independent on the initial conditions. The validity of the proposed model has been examined by numerical simulations.

This paper presented a brief description for the gait planning of quadruped robot named Aibo ERS-7 which is a standard platform in the RoboCup 4-legged league. We approach a spline shaped locus to reduce the dimension of the parameter optimizing space and solve the problem of the significant bias between the planned locus and the real one. The result shows that the spline shaped locus is effective in finding the optimized locus shape in a short time. Finally, the robot achieves a gait faster than any previously known learned gait for Aibo

For conventional fuzzy systems, Mamdani type or TS type, it is; well known that the number of fuzzy rules and adjustable parameters exponentially increases with the number of input variables. This problem is often referred as curse of dimensionality. Hierarchical fuzzy systems have been proposed to resolve this problem. At present, however, it is unclear whether or not hierarchical fuzzy systems can truly resolve this issue. In this paper, we investigate the zero-order TS fuzzy systems and their corresponding hierarchical fuzzy systems. We rigorously prove that to approximate any continuous functions with the same degree of accuracy, the number of parameters used by the hierarchical fuzzy systems are exactly the same as those employed by the TS systems. This result implies that the hierarchical fuzzy systems do not offer a real solution, at least for the zero-order TS fuzzy systems

A web object is defined to represent any meaningful object embedded in web pages (e.g. images, music) or pointed to by hyperlinks (e.g. downloadable files). In many cases, users would like to search for information of a certain 'object', rather than a web page containing the query terms. To facilitate web object searching and organizing, in this paper, we propose a novel approach to web object indexing, by discovering its inherent structure information with existed domain knowledge. In our approach, first, Layered LSI spaces are built for a better representation of the hierarchically structured domain knowledge, in order to emphasize the specific semantics and term space in each layer of the domain knowledge. Meanwhile, the web object representation is constructed by hyperlink analysis, and further pruned to remove the noises. Then an optimal matching between the web object and the domain knowledge is performed, in order to pick out the structure attributes of the web object from the knowledge. Finally, the obtained structure attributes are used to re-organize and index the web objects. Our approach also indicates a new promising way to use trust-worthy Deep Web knowledge to help organize dispersive information of Surface Web.

In this paper, a fuzzy associative memory scheme is thoroughly investigated and modified. Based on the existing fuzzy associative memory structure and algorithms, a genetic algorithm was used to adjust the parameters in the membership function of the fuzzy controller. Simulation experiments based on the inverted pendulum have proved the feasibility and adaptability of the new scheme.

In this paper, the authors present a new self-learning fuzzy neural network controller based on reference model. Based on the difference between the output of the reference model and that of the real control process, a gradient descent learning algorithm completes the real-time online modification of the parameters of the fuzzy-neural network hybrid system. The simulation experiments based on the inverted pendulum proved the effectiveness and performance of this new scheme.