3D Engineering Model Retrieval Based on Enhanced Shape Distributions

To reuse and share the valuable knowledge embedded in repositories of engineering models for accelerating the design process, improving product quality, and reducing costs, it is crucial to devise search engines capable of matching 3D models efficiently and effectively. In this paper, an enhanced shape distributions-based technique of using geometrical and topological information to search 3D engineering models represented by polygonal meshes was presented. A simplification method of polygonal meshes was used to simplify engineering model as the pretreatment for generation of sample points. The method of sampling points was improved and a pair of functions that was more sensitive to shape was employed to construct a 2D shape distribution. Experiments were conducted to evaluate the proposed algorithm utilizing the Engineering Shape Benchmark (ESB) database. The experiential results suggest that the search effectiveness is significantly improved by enforcing the simplification and enhanced shape distributions to engineering model retrieval.

Support Vector Machine active learning for 3D model retrieval

In this paper, we present a novel Support Vector Machine active learning algorithm for effective 3D model retrieval using the concept of relevance feedback. The proposed method learns from the most informative objects which are marked by the user, and then creates a boundary separating the relevant models from irrelevant ones. What it needs is only a small number of 3D models labelled by the user. It can grasp the user＇s semantic knowledge rapidly and accurately. Experimental results showed that the proposed algorithm significantly improves the retrieval effectiveness. Compared with four state-of-the-art query refinement schemes for 3D model retrieval, it provides superior retrieval performance after no more than two rounds of relevance feedback.

High Efficient Methods of Content-based 3D Model Retrieval

Content-based 3D model retrieval is of great help to facilitate the reuse of existing designs and to inspire designers during conceptual design. However, there is still a gap to apply it in industry due to the low time efficiency. This paper presents two new methods with high efficiency to build a Content-based 3D model retrieval system. First, an improvement is made on the ＂Shape Distribution （D2）＂ algorithm, and a new algorithm named ＂Quick D2＂ is proposed. Four sample 3D mechanical models are used in an experiment to compare the time cost of the two algorithms. The result indicates that the time cost of Quick D2 is much lower than that of D2, while the descriptors extracted by the two algorithms are almost the same. Second, an expandable 3D model repository index method with high performance, namely, RBK index, is presented. On the basis of RBK index, the search space is pruned effectively during the search process, leading to a speed up of the whole system. The factors that influence the values of the key parameters of RBK index are discussed and an experimental method to find the optimal values of the key parameters is given. Finally, ＂3D Searcher＂, a content-based 3D model retrieval system is developed. By using the methods proposed, the time cost for the system to respond one query online is reduced by 75% on average. The system has been implemented in a manufacturing enterprise, and practical query examples during a case of the automobile rear axle design are also shown. The research method presented shows a new research perspective and can effectively improve the content-based 3D model retrieval efficiency.

EFFECT OF SUBMERGED ENTRY NOZZLE (SEN) PARAMETERS AND SHAPE ON 3-D FLUID FLOW IN MOULD FOR BEAM BLANK CONTINUOUS CASTING

According to turbulent theory and characteristics of beam blank continuous casting, 3-D model to represent the flow of beam blank mould is established. The predicted results indicate that the exit obliquity of up 15°(+15°) should be adopted, which will benefit the floatation of non-metallic inclusion and purification of the molten steel. When the nozzle angle is 120°, the flow pattern is reasonable. Proper nozzle depth can be 200mm. Turbulent kinetic of meniscus can be reduced by adopting the square nozzle and suitable area of side outlet when casting speed increases. The results are consistent with those of water model experiment, so the model is exact and reasonable. The model can provide important information for design of SEN and defining of immersion depth.

ACQUIREMENT AND COMPUTER PROCESSING OF 3-D SURFACE SHAPE DATA

The laser scanning and CCD image-transmitting measurement method and principle on acquiring 3-D curved surface shape data are discussed. Computer processing technique of 3-D curved surface shape(be called“ 3 - D surface shape”for short) data is analysed. This technique in- cludes these concrete methods and principles such as data smoothing, fitting, reconstructing ,elimi- nating and so on. The example and result about computer processing of 3- D surface shape data are given .

Part-level 3-D object classification with improved interpretation tree

For classifying unknown 3-D objects into a set of predetermined object classes, a part-level object classification method based on the improved interpretation tree is presented. The part-level representation is implemented, which enables a more compact shape description of 3-D objects. The proposed classification method consists of two key processing stages： the improved constrained search on an interpretation tree and the following shape similarity measure computation. By the classification method, both whole match and partial match with shape similarity ranks are achieved; especially, focus match can be accomplished, where different key parts may be labeled and all the matched models containing corresponding key parts may be obtained. A series of experiments show the effectiveness of the presented 3-D object classification method.

STRUCTURE OF MESO-β AND –γ-SCALE ON SOUTH CHINA HEAVY RAINFALL ON 12～13 JUNE 2005 USING DUAL-DOPPLER RADAR

The three-dimensional wind fields of the heavy rain on 12-13 June 2005 in Guangdong province are retrieved and studied with the volume scan data of the dual-Doppler radar located in the cities of Meizhou and Shantou. It is shown that the meso-β-scale and meso-γ-scale convergence lines located in the convective system at the low and middle layer play an important role in the heavy rainfall. The convergence line is the initiating and maintaining mechanism of the rain. A three dimensional kinematic structure model is also given.

A Survey on Partial Retrieval of 3D Shapes

Content-based shape retrieval techniques can facilitate 3D model resource reuse, 3D model modeling, object recognition, and 3D content classification. Recently more and more researchers have attempted to solve the problems of partial retrieval in the domain of computer graphics, vision, CAD, and multimedia. Unfortunately, in the literature, there is little comprehensive discussion on the state-of-the-art methods of partial shape retrieval. In this article we focus on reviewing the partial shape retrieval methods over the last decade, and help novices to grasp latest developments in this field. We first give the definition of partial retrieval and discuss its desirable capabilities. Secondly, we classify the existing methods on partial shape retrieval into three classes by several criteria, describe the main ideas and techniques for each class, and detailedly compare their advantages and limits. We also present several relevant 3D datasets and corresponding evaluation metrics, which are necessary for evaluating partial retrieval performance. Finally, we discuss possible research directions to address partial shape retrieval.

Efficient View-Based 3-D Object Retrieval via Hypergraph Learning

View-based 3-D object retrieval has become an emerging topic in recent years,especially with the fast development of visual content acquisition devices,such as mobile phones with cameras.Extensive research efforts have been dedicated to this task,while it is still difficult to measure the relevance between two objects with multiple views.In recent years,learning-based methods have been investigated in view-based 3-D object retrieval,such as graph-based learning.It is noted that the graph-based methods suffer from the high computational cost from the graph construction and the corresponding learning process.In this paper,we introduce a general framework to accelerate the learning-based view-based 3-D object matching in large scale data.Given a query object Q and one object O from a 3-D dataset D,the first step is to extract a small set of candidate relevant 3-D objects for object O.Then multiple hypergraphs can be constructed based on this small set of 3-D objects and the learning on the fused hypergraph is conducted to generate the relevance between Q and O,which can be further used in the retrieval procedure.Experiments demonstrate the effectiveness of the proposed framework.

Joint shape and color descriptors for 3D urban model retrieval

With the rapid development of photogrammetry,computer vision and three-dimensional(3D)modeling technologies,it is possible to efficiently construct detailed 3D urban models.Accordingly,large corpora of 3D models,such as the Google 3D Warehouse,are now becoming freely available on the web.How to find the proper 3D urban models is a challenging research issue.In this paper,we join shape descriptors and color descriptors for 3D urban model retrieval.The query objects are localized and segmented automatically from the input images by using a new selective search voting algorithm.Through combining the normalization with the light field descriptor,the Horizontal Light Descriptor is introduced to measure the shape similarity among the normalized urban models.The color descriptors are used to represent the color information of the urban models.The two types of descriptors are joined to search 3D urban models similar to the query objects.Experimental results have shown the effectiveness of our approach.

3D object retrieval based on histogram of local orientation using one-shot score support vector machine

In this paper, a content based descriptor is pro- posed to retrieve 3D models, which employs histogram of local orientation （HLO） as a geometric property of the shape. The proposed 3D model descriptor scheme consists of three steps. In the first step, Poisson equation is utilized to define a 3D model signature. Next, the local orientation is calculated for each voxel of the model using Hessian matrix. As the final step, a histogram-based 3D model descriptor is extracted by accumulating the values of the local orientation in bins. Due to efficiency of Poisson equation in describing the models with various structures, the proposed descriptor is capable of discriminating these models accurately. Since, the inner vox- els have a dominant contribution in the formation of the de- scriptor, sufficient robustness against noise can be achieved. This is because the noise mostly influences the boundary vox- els. Furthermore, we improve the retrieval performance us- ing support vector machine based one-shot score （SVM-OSS） similarity measure, which is more efficient than the conven- tional methods to compute the distance of feature vectors. The rotation normalization is performed employing the prin- cipal component analysis. To demonstrate the applicability of HLO, we implement experimental evaluations of precision- recall curve on ESB, PSB and WM-SHREC databases of 3D models. Experimental results validate the effectiveness of the proposed descriptor compared to some current methods.

3-D Shape Measurement of Complex Objects by Combining Color-Coded Fringe and Neural Networks

A new approach for three dimensional (3-D) shape measurement was proposed based on colorcoded fringe and neural networks. By applying the phase-shift technique to fringe projection, point clouds were generated with high spatial resolution and limited accuracy. The picture element correspondence problem was solved by using projected color-coded fringes with different orientations. Once the high accurate corresponding points were decided, high precision dense 3-D points cloud was calculated by the well trained net. High spatial resolution can be obtained by the phase-shift technique and high accuracy 3-D object point coordinates are achieved by the well trained net, which is not dependent on the camera model and will work for any type of camera. Some experiments verify the performance of this method.

基于距离-夹角形状分布的三维CAD模型检索算法

为了更好地实现三维CAD模型的有效重用,提出一种三维CAD模型距离-夹角形状分布检索算法。首先在CAD模型表面随机取点,计算任意两点构成的有向线段的距离和该有向线段与端点法向的夹角;然后以距离和夹角为坐标轴构建距离-夹角平面网格,统计网格中随机点出现的频次,从而构建模型的距离-夹角分布矩阵;最后采用Manhattan距离度量法计算矩阵的相似值,用以评价模型间的相似程度。实验结果表明,该算法可以较好地实现三维CAD模型检索,检索性能优于已有的形状分布检索算法,能够满足实际应用需求。

Technical features in the Portal to CADAL

China-America Digital Academic Library Project (CADAL) is a collaborative project between universities and institutes in China and the USA, which aims to provide universal access to large scale digital resources and explore the ways of applying multimedia and virtual reality technologies to digital library. The distinct characteristic of the resources in CADAL is that it not only contains one million digital books of different languages, but also contains Terabyte level multimedia resources (image, video, and so on), which are utilized for education and research purposes. So, in the Portal to CADAL, both the traditional services of browsing and searching of digital books, and the services of quickly retrieving and structurally browsing of multimedia documents should be provided. In addition, the services of visual presentation of retrieved results are required too. In this paper, the underlying novel multimedia retrieval methods as well as visualization techniques, which are used in the CADAL portal, are investigated.

THREE DIMENSIONAL DIGITIZATION OF HUMAN HEAD BY FUSING STRUCTURED LIGHT AND CONTOURS

Three dimensional digitization of human head is desired in many applications. In this paper, an information fusion based scheme is presented to obtain 3-D information of human head. Structured light technology is employed to measure depth. For the special reflection areas,in which the structured light stripe can not be detected directly, the shape of the structured light stripe can be calculated from the corresponding contour. By fusing the information of structured light and the contours, the problem of reflectance influence is solved, and the whole shape of head,including hair area, can be obtained. Some good results are obtained.

Geometric and Photometric Data Fusion in Non-Rigid Shape Analysis

In this paper,we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local and global shape descriptors.Our construction is based on the definition of a diffusion process on the shape manifold embedded into a high-dimensional space where the embedding coordinates represent the photometric information.Experimental results show that such data fusion is useful in coping with different challenges of shape analysis where pure geometric and pure photometric methods fail.

基于先验知识的三维模型特征选择算法

基于内容的三维模型检索被广泛运用于许多研究领域。为了弥补特征提取算法描述模型特征的不足,提高三维模型的检索效果,该文提出了一种基于先验知识的三维模型特征向量动态选择算法。该算法利用查询模型计算各种特征向量的先验知识,然后动态地选择描述能力较强的特征向量计算模型之间的相似度距离。实验采用标准的模型库Princeton shape benchmark(PSB)和多种公认的评价方法,结果显示该算法提高了三维模型的检索效果,优于现有的2种流行的三维模型特征选择算法。

A Parallel Voting Scheme for Aspect Recovery

Recently, a qualitative approach was proposed for 3-D shape recovery based on a hybrid object representation[1]. In this approach, aspect recovery is the most important stage which binds regions in the image into meaningful aspects to support 3-D primitive recovery. There is no known polynondal time algo-rithm to solve this problem. The previous approach dealt with this problem by using a heuristic method based on the conditional probability. Unlike the previous method, this paper presents a novel parallel voting scheme to conquer the problem for efficiency. For this purpose) the previous global aspect rep-resentation is replaced with a distributed representation of aspects. Based on this representation, a three-layer parallel voting network for aspect recovery is proposed. For evaluating likelihood, a continuous Hopfield net is employed so that all aspect coverings in decreasing order of likelihood can be enumerated.The paper describes this method in detail and demonstrates its usefulness with simulation.