DanVideo: an MPEG-7 authoring and retrieval system for dance videos

A well-annotated dance media is an essential part of a nation’s identity, transcending cultural and language barriers. Many dance video archives suffer from problems concerning authoring and access, because of the complex spatio-temporal relationships that exist between the dancers in terms of movements of their body parts and the emotions expressed by them in a dance. This paper presents a system named DanVideo for semi-automatic authoring and access to dance archives. DanVideo provides methods of annotation and authoring and retrieval tools for choreographers, dancers, and students. We demonstrate how dance media can be semantically annotated and how this information can be used for the retrieval of the dance video semantics. In particular, DanVideo offers an MPEG-7 based semi-automatic authoring tool that takes dance video annotations generated by dance experts and produces MPEG-7 metadata. DanVideo also has a search engine that takes users’ queries and retrieves dance semantics from metadata arranged using tree-embedding technique and based on spatial, temporal and spatio-temporal features of dancers. The search engine also leverages a domain-specific ontology to process knowledge-based queries. We have assessed the dance-video queries and semantic annotations in terms of precision, recall, and fidelity.     

A semantic framework for metamodel-based languages

In the model-based development context, metamodel-based languages are increasingly being defined and adopted either for general purposes or for specific domains of interest. However, meta-languages such as the MOF (Meta Object Facility)—combined with the OCL (Object Constraint Language) for expressing constraints—used to specify metamodels focus on structural and static semantics but have no built-in support for specifying behavioral semantics. This paper introduces a formal semantic framework for the definition of the semantics of metamodel-based languages. Using metamodelling principles, we propose several techniques, some based on the translational approach while others based on the weaving approach, all showing how the Abstract State Machine formal method can be integrated with current metamodel engineering environments to endow language metamodels with precise and executable semantics. We exemplify the use of our semantic framework by applying the proposed techniques to the OMG metamodelling framework for the behaviour specification of the Finite State Machines provided in terms of a metamodel.     

A compositional semantics of UML-RSDS

This paper provides a semantics for the UML-RSDS (Reactive System Development Support) subset of UML, using the real-time action logic (RAL) formalism. We show how this semantics can be used to resolve some ambiguities and omissions in UML semantics, and to support reasoning about specifications using the B formal method and tools. We use ‘semantic profiles’ to provide precise semantics for different semantic variation points of UML. We also show how RAL can be used to give a semantics to notations for real-time specification in UML. Unlike other approaches to UML semantics, which concentrate on the class diagram notation, our semantic representation has behaviour as a central element, and can be used to define semantics for use cases, state machines and interactions, in addition to class diagrams.     

Constructing language processors with algebra combinators

Modular Monadic Semantics (MMS) is a well-known mechanism for structuring modular denotational semantic definitions for programming languages. The principal attraction of MMS is that families of language constructs can be independently specified and later combined in a mix-and-match fashion to create a complete language semantics. This has proved useful for constructing formal, yet executable, semantics when prototyping languages. In this work we demonstrate that MMS has an additional software engineering benefit. In addition to composing semantics for various language constructs, we can use MMS to compose various differing semantics for the same language constructs. This capability allows us to compose and reuse orthogonal language tasks such as type checking and compilation. We describe algebra combinators, the principal vehicle for achieving this reuse, along with a series of applications of the technique for common language processing tasks.     

A real-time profile for UML

This paper describes an approach for real-time modelling in UML, focusing on analysis and verification of time and scheduling-related properties. To this aim, a concrete UML profile, called the ωprofile, is defined, dedicated to real-time modelling by identifying a set of relevant concepts for real-time modelling which can be considered as a refinement of the standard SPT profile. The profile is based on a rich concept of event representing an instant of state change, and allows the expression of duration constraints between occurrences of events. These constraints can be provided in the form of OCL-like expressions annotating the specification or by means of state machines, stereotyped as ‘observers’. A framework for modelling scheduling issues is obtained by adding a notion of resource and a notion of execution time. For proving the relevance of these choices, the profile has been implemented in a validation tool and applied to case studies. It has a formal semantics and is sufficiently general and expressive to define a semantic underpinning for other real-time profiles of UML which in general define more restricted frameworks. In particular, most existing profiles handling real-time issues define a number of predefined attributes representing particular durations or constraints on them and their semantic interpretation can be expressed in the OMEGA-RT profile. This work has been partially supported by the IST-2002-33522 OMEGA project. VERIMAG is an academic research laboratory associated with CNRS, Université Joseph Fourier and Institut Nationale Polytechnique de Grenoble.     

Mapping DTDs to relational schemas with semantic constraints

XML is becoming a prevalent format and standard for data exchange in many applications. With the increase of XML data, there is an urgent need to research some efficient methods to store and manage XML data. As relational databases are the primary choices for this purpose considering their data management power, it is necessary to research the problem of mapping XML schemas to relational schemas. The semantics of XML schemas are crucial to design, query, and store XML documents and functional dependencies are very important representations of semantic information of XML schemas. As DTDs are one of the most frequently used schemas for XML documents in these days, we will use DTDs as schemas of XML documents here. This paper proposes the concept and the formal definition of XML functional dependencies over DTDs. A method to map XML DTDs to relational schemas with constraints such as functional dependencies, domain constraints, choice constraints, reference constraints, and cardinality constraints over DTDs is given, which can preserve the structures of DTDs as well as the semantics implied by the above constraints over DTDs. The concepts and method of mapping DTDs to relational schemas presented in the paper can be extended to the field of XML Schema just with some modifications in related formal definitions.     

一种基于语义的视频场景分割算法

针对如何在镜头基础上进行聚类，以得到更高层次的场景问题，提出了一个基于语义的场景分割算法。该算法首先将视频分割为镜头，并提取镜头的关键帧。然后计算关键帧的颜色直方图和MPEG-7边缘直方图，以形成关键帧的特征；接着利用镜头关键帧的颜色和纹理特征对支持向量机（SVM）进行训练来构造7个基于SVM对应不同语义概念的分类器，并利用它们对要进行场景分割的视频镜头关键帧进行分类，以得到关键帧的语义。并根据关键帧包含的语义概念形成了其语义概念矢量，最后根据语义概念矢量通过对镜头关键帧进行聚类来得到场景。另外．为提取场景关键帧，还构建了镜头选择函数，并根据该函数值的大小来选择场景的关键帧。实验结果表明，该场景分割算法与Hanjalic的方法相比，查准率和查全率分别提高了34．7％和9．1％。     

基于MPEG-7的视频语义检索系统

设计和实现一个支持语义的分布式视频检索系统:"语寻"。该系统利用一个改进的视频语义处理工具(该工具基于IBM VideoAnnEx标注工具,并增加镜头语义图标注和自然语言处理的功能)对视频进行语义分析和标注,生成包含语义信息的MPEG-7描述文件,然后对视频的MPEG-7描述文件建立分布式索引,并同时分布式存储视频文件;系统提供丰富的Web查询接口,包括关键字语义扩展查询,语义图查询以及自然语句查询,当用户提交语义查询意图后,便能够迅速地检索到感兴趣的视频和片段,并且可以浏览点播;整个系统采用分布式架构,具备良好的可扩展性,并能够支持海量视频信息的索引和检索。     

Model-Based Video Classification toward Hierarchical Representation,Indexing and Access

In this paper, we develop a content-based video classification approach to support semantic categorization, high-dimensional indexing and multi-level access. Our contributions are in four points: (a) We first present a hierarchical video database model that captures the structures and semantics of video contents in databases. One advantage of this hierarchical video database model is that it can provide a framework for automatic mapping from high-level concepts to low-level representative features. (b) We second propose a set of useful techniques for exploiting the basic units (e.g., shots or objects) to access the videos in database. (c) We third suggest a learning-based semantic classification technique to exploit the structures and semantics of video contents in database. (d) We further develop a cluster-based indexing structure to both speed-up query-by-example and organize databases for supporting more effective browsing. The applications of this proposed multi-level video database representation and indexing structures for MPEG-7 are also discussed.