基于相似性序列分析的三维模型检索性能评价

普林斯顿形状基准数据库已经成为当前三维模型检索研究人员使用最为广泛的基准数据库之一。但是该基准数据库存在着一个重要的缺陷,那便是模型类别之间的相似性没有被考虑,这导致在对检索结果进行性能评价时出现与人类直观感觉不一致的结论。为了克服这个缺陷,提出了一种新的基准数据库分类方案,并且在此基础上提出了一种基于相似性序列分析的检索性能评估方法。     

面向内容的三维人体运动检索技术研究综述

三维人体运动数据检索技术是计算机动画领域的研究热点,系统分析了当前基于内容的三维人体运动数据检索技术的研究现状。分析比较了基于运动数值特征、基于运动能量特征和基于语义信息特征三种运动数据的特征表示方法;从局部相似性度量和全局相似性判断两个角度阐述了运动相似性匹配算法;总结目前基于内容的人体运动数据检索技术中存在的问题,探讨了未来开展基于语义的检索技术所需的工作。     

Assessing similarity models for human‐motion retrieval applications

The development of motion capturing devices poses new challenges in the exploitation of human‐motion data for various application fields, such as computer animation, visual surveillance, sports, or physical medicine. Recently, a number of approaches dealing with motion data have been proposed, suggesting characteristic motion features to be extracted and compared on the basis of similarity. Unfortunately, almost each approach defines its own set of motion features and comparison methods; thus, it is hard to fairly decide which similarity model is the most suitable for a given kind of human‐motion retrieval application. To cope with this problem, we propose the human motion model evaluator, which is a generic framework for assessing candidate similarity models with respect to the purpose of the target application. The application purpose is specified by a user in form of a representative sample of categorized motion data. Respecting such categorization, the similarity models are assessed from the effectiveness and efficiency points of view using a set of space‐complexity, information‐retrieval, and performance measures. The usability of the framework is demonstrated by case studies of three practical examples of retrieval applications focusing on recognition of actions, detection of similar events, and identification of subjects. Copyright © 2015 John Wiley & Sons, Ltd.     

改进的三维模型形状分布检索算法

针对传统D1距离形状分布函数获取采样点计算复杂、模型内容描述不充分和检索速率低下等问题提出了一种改进方法。该方法的关键点是：首先采用平移和缩放对模型进行标准化处理,用于减少面片之间的差异,使得采样点均匀地落在模型的表面;其次采用三角面片的索引号进行随机数的生成,并且利用三角面片的重心和质心进行有效的计算,以便用于缩短模型的处理时间和提高检索速率。利用普林斯顿大学三维模型数据库中的部分模型作为实验数据,实现结果表明：改进的方法不会降低模型的检索性能,并有效地减少了模型查询和处理时间。     

A real-time system for motion retrieval and interpretation

This paper proposes a new examplar-based method for real-time human motion recognition using Motion Capture (MoCap) data. We have formalized streamed recognizable actions, coming from an online MoCap engine, into a motion graph that is similar to an animation motion graph. This graph is used as an automaton to recognize known actions as well as to add new ones. We have defined and used a spatio-temporal metric for similarity measurements to achieve more accurate feedbacks on classification. The proposed method has the advantage of being linear and incremental, making the recognition process very fast and the addition of a new action straightforward. Furthermore, actions can be recognized with a score even before they are fully completed. Thanks to the use of a skeleton-centric coordinate system, our recognition method has become view-invariant. We have successfully tested our action recognition method on both synthetic and real data. We have also compared our results with four state-of-the-art methods using three well known datasets for human action recognition. In particular, the comparisons have clearly shown the advantage of our method through better recognition rates.     

Non-rigid 3D shape tracking from multiview video

We present a fast and efficient non-rigid shape tracking method for modeling dynamic 3D objects from multiview video. Starting from an initial mesh representation, the shape of a dynamic object is tracked over time, both in geometry and topology, based on multiview silhouette and 3D scene flow information. The mesh representation of each frame is obtained by deforming the mesh representation of the previous frame towards the optimal surface defined by the time-varying multiview silhouette information with the aid of 3D scene flow vectors. The whole time-varying shape is then represented as a mesh sequence which can efficiently be encoded in terms of restructuring and topological operations, and small-scale vertex displacements along with the initial model. The proposed method has the ability to deal with dynamic objects that may undergo non-rigid transformations and topological changes. The time-varying mesh representations of such non-rigid shapes, which are not necessarily of fixed connectivity, can successfully be tracked thanks to restructuring and topological operations employed in our deformation scheme. We demonstrate the performance of the proposed method both on real and synthetic sequences.     

A survey of content based 3D shape retrieval methods

Recent developments in techniques for modeling, digitizing and visualizing 3D shapes has led to an explosion in the number of available 3D models on the Internet and in domain-specific databases. This has led to the development of 3D shape retrieval systems that, given a query object, retrieve similar 3D objects. For visualization, 3D shapes are often represented as a surface, in particular polygonal meshes, for example in VRML format. Often these models contain holes, intersecting polygons, are not manifold, and do not enclose a volume unambiguously. On the contrary, 3D volume models, such as solid models produced by CAD systems, or voxels models, enclose a volume properly. This paper surveys the literature on methods for content based 3D retrieval, taking into account the applicability to surface models as well as to volume models. The methods are evaluated with respect to several requirements of content based 3D shape retrieval, such as: (1) shape representation requirements, (2) properties of dissimilarity measures, (3) efficiency, (4) discrimination abilities, (5) ability to perform partial matching, (6) robustness, and (7) necessity of pose normalization. Finally, the advantages and limitations of the several approaches in content based 3D shape retrieval are discussed.