A survey on content-based retrieval for multimedia databases <s> CBR by Derivation Knowledge <s> A knowledge-based database assistant (KDA) which integrates a natural language query system with a skeleton-based query guiding facility is provided. When a user works with the KDA natural language query system, the query guiding facility can supply several kinds of skeletons to guide users in performing database retrieval tasks. A semantic network model, S-Net, is introduced to represent the knowledge for natural language query processing and skeleton generation. Methods for implementing the system are discussed. > <s> BIB001 </s> A survey on content-based retrieval for multimedia databases <s> CBR by Derivation Knowledge <s> The complex nature of two-dimensional image data has presented problems for traditional information systems designed strictly for alphanumeric data. Systems aimed at effectively managing image data have generally approached the problem from two different views: They either possess a strong database component with little image understanding, or they serve as an image repository for computer vision applications, with little emphasis on the image retrieval process. A general architecture for visual information-management systems (VIMS), which combine the strengths of both approaches, is presented. The system utilizes computer vision routines for both insertion and retrieval and allows easy query-by-example specifications. The vision routines are used to segment and evaluate objects based on domain-knowledge describing the objects and their attributes. The vision system can then assign feature values to be used for similarity-measures and image retrieval. A VIMS developed for face-image retrieval is presented to demonstrate these ideas. > <s> BIB002 </s> A survey on content-based retrieval for multimedia databases <s> CBR by Derivation Knowledge <s> In accordance with the progress of data management ability of computers, databases have become able to integrate various types of data in an application domain, and are now called multimedia databases. Unlike conventional databases managing only textual and numerical data, multimedia databases are required to evaluate properties of the data specified in a query. In this paper, a system which enables querying with the facility of acquiring the contents of multiple types of data is presented. Domain Knowledge accommodated in the system gives the information on how the system views the target multimedia data for content-based retrieval attaining application-independency as well as media-independency. > <s> BIB003 </s> A survey on content-based retrieval for multimedia databases <s> CBR by Derivation Knowledge <s> Proposes an image database with a fully automated keyword extraction function. Our approach can extract two different conceptual-level keywords from images. One is the "conceptual keyword", which is extracted by an image recognition technique using the "state transition model", which is a hierarchical model. The other keyword is the "scene description keyword", which is extracted by primitive parameters of color segments. We also propose the introduction of a "transition probability" to raise the retrieval accuracy (precision). Moreover, we evaluate the retrieval accuracy of this image database through a retrieval experiment using about 170 scenery images. <s> BIB004 </s> A survey on content-based retrieval for multimedia databases <s> CBR by Derivation Knowledge <s> Content based browsing and navigation in digital video collections have been centered on sequential and linear presentation of images. To facilitate such applications, nonlinear and non sequential access into video documents is essential, especially with long programs. For many programs, this can be achieved by identifying underlying story structures which are reflected both by visual content and temporal organization of composing elements. A new framework of video analysis and associated techniques are proposed to automatically parse long programs, to extract story structures and identify story units. The proposed analysis and representation contribute to the extraction of scenes and story units, each representing a distinct locale or event, that cannot be achieved by shot boundary detection alone. Analysis is performed on MPEG compressed video and without a prior models. The result is a compact representation that serves as a summary of the story and allows hierarchical organization of video documents. <s> BIB005 </s> A survey on content-based retrieval for multimedia databases <s> CBR by Derivation Knowledge <s> Image/video data contains numerous information such as objects, image attributes (e.g., color, height, width) of objects, and various semantic contents. Provision of a scheme for the retrieval of video data content is still one of the unfulfilled issues. The authors propose a method of retrieving video data from films by way of specifying the semantic content of scenes. Related to the creation of films, there is a so-called "the grammar of film", which is an accumulation of knowledge and rules for expressing certain semantics of a scene more effectively. They concentrate on the features of video that can be observed as a consequence of the effects of the grammar of film. Since the features relate to shot length, the degree of image dynamics of shots, or the combination of similar shots, this method is less time-consuming than other ways of evaluating sequences of images in detail. <s> BIB006 </s> A survey on content-based retrieval for multimedia databases <s> CBR by Derivation Knowledge <s> This paper discusses a video cut detection method. Cut detection is an important technique for making videos easier to handle. First, this paper analyzes the distribution of the image differenceV to clarify the characteristics that makeV suitable for cut detection. We propose a cut detection method that uses a projection (an isolated sharp peak) detecting filter. A motion sensitiveV is used to stabilizeV projections at cuts, and cuts are detected more reliably with this filter. The method can achieve high detection rates without increasing the rate of misdetection. Experimental results confirm the effectiveness of the filter. <s> BIB007
Another method of implementing 'query-by-subject/object' is to provide the system with a rule base or a knowledge base. The knowledge-based approach for text databases has a long history than that for multimedia databases. In that area, the main interest is not only in generating cooperative answers BIB001 but also in retrieving semantic contents implied in the text  ,  . In the area of CBR for multimedia databases, BIB003 , BIB004 study the content-based retrieval of images using knowledge that interprets semantic contents into image representations. The content to be retrieved concerns the meaning of an image that is represented by a keyword. Under the assumption that objects appearing in the image are already known, semantic contents that relate to the attribute value of the objects are also in the target of retrieval BIB002 . In BIB003 , Domain Knowledge defines the method for extracting semantic features from multimedia data such as, images, rules to transform a certain operator into contentdependent calculus, and rules for transforming query conditions into an internal representation whose type is the same as the extracted semantic features. A definition of pseudo attribute associates a query condition with a domain knowledge describing the contents to be retrieved (Fig. 5) . In BIB004 , a keyword is defined with a description that denotes image features such as regions of colors and their location. A state transition model defines a hierarchical relation between primitive color regions and semantic contents represented by the spatial composition of color regions. With these approaches, images are retrieved by a content based on image features specific to the content. Hsu et al.  is also an example applying knowledgebased CBR to a medical image. Knowledge is referred to for the evaluation of shapes and spatial relations of objects (in the application, it is tumor), and image semantics. Knowledge for interpreting contents on spatial relations or semantic contents is constructed by Type Abstraction Hierarchy (TAH). TAH defines a general level of concepts to detailed level with sets of attribute values. In these studies, semantic contents are represented by knowledge directly, in the sense that the knowledge associated with feature values and/or spatial relations are the fundamental property of the contents. In contrast to this knowledge-based CBR, there is another approach of defining knowledge for the subject of interest indirectly BIB006 . In BIB006 , the semantic expression of the contents of a scene, such as the scene of conversation or the scene of tension, are associated with camera framing and/or editing technique commonly applied by film directors or editors, which is the so called "film grammar." Note that camera framing and film editing does not directly represent semantic contents such as conversation or scene on tenterhooks, nor tries to extract from the database system the faces of person for evaluating a conversation scene. That is, such semantic contents themselves are not extracted from video data, but the editorial technique is extracted to evaluate the semantic contents. Prior to the extraction of scene features, the process of cut detection BIB007 or extraction of scene unit BIB005 is mandatory for automated parsing of video data.