We present a framework for content based query and retrieval of information from large videodatabases. This framework enables content based retrieval of video sequences by characterizing the sequences using motion, t...
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We present a framework for content based query and retrieval of information from large videodatabases. This framework enables content based retrieval of video sequences by characterizing the sequences using motion, texture and colorimetry cues. This characterization is biologically inspired and results in a compact parameter space where every segment of video is represented by an 8 dimensional vector. Searching and retrieval is done in real-time with high accuracy in this parameter space. The present version of the videoBook has 165 video sequences, each 15 seconds long at 30 frames a second representing storage of 65 Giga bytes. The videoBook is able to search and retrieve video sequences with 92% accuracy in real-time. Experiments thus demonstrate that the characterization is capable of extracting higher level structure from raw pixel values.
This paper presents a model-based form processing sub-system, which consists of a form model database and five modules: (i) form modeling, (ii) form recognition, (iii) form dropout, (iv) form definition tool, and (v) ...
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ISBN:
(纸本)081867282X
This paper presents a model-based form processing sub-system, which consists of a form model database and five modules: (i) form modeling, (ii) form recognition, (iii) form dropout, (iv) form definition tool, and (v) form reconstruction. The form modeling module builds explicit representations of scanned form templates to facilitate form recognition and dropout. It can also assist a user to define various fields on a form. The automatic form recognition eliminates the need for manually sorting input forms. The form dropout module effectively removes pre-printed form content to achieve a high data compression rate and to provide clean data for OCR. Our model-driven form dropout scheme has two major advantages over image-based subtraction methods in both dropout efficiency and quality preservation of filled-in data.
The proceedings contains 40 papers. Some of the specific topics discussed are: feature identification as an aid to content-based imageretrieval;scheme for visual feature-based image indexing;techniques for data hidin...
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ISBN:
(纸本)081941767X
The proceedings contains 40 papers. Some of the specific topics discussed are: feature identification as an aid to content-based imageretrieval;scheme for visual feature-based image indexing;techniques for data hiding;searching images using multimedia manager;databases for video information sharing;statistical approach to scene change detection;image indexing using vector quantization;and similarity of color images.
This paper describes the videoSTAR experimental database system that is being designed to support video applications in sharing and reusing video data and meta-data. videoSTAR provides four different repositories: for...
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ISBN:
(纸本)081941767X
This paper describes the videoSTAR experimental database system that is being designed to support video applications in sharing and reusing video data and meta-data. videoSTAR provides four different repositories: for media files, virtual documents, video structures, and video annotations/user indexes. It also provides a generic video data model relating data in the different repositories to each other, and it offers a powerful application interface. videoSTAR concepts have been evaluated by developing a number of experimental video tools, such as a video player, a video annotator, a video authoring tool, a video structure and contents browser, and a video query tool.
In this paper, we study the possibility of using Θ-index for retrieval of imagebase. imageretrieval is related to partition in an image space. If there exists a mapping from an image space to a feature space, the pa...
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ISBN:
(纸本)081941767X
In this paper, we study the possibility of using Θ-index for retrieval of imagebase. imageretrieval is related to partition in an image space. If there exists a mapping from an image space to a feature space, the partition in the image space can be converted into a partition in the feature space. To retrieve an image, some features of the image must be identified. Feature identification can be considered as optimal assignment of some indices to images. This is equivalent to an optimal partition of image space into mutual exclusive regions, each corresponding to particular values of a set of indices. In our system, the feature extraction is implemented by a two-dimensional Θ-transformation. The time complexity for a Θ-transformation is very low. Therefore, for a certain class of images, Θ- transformation is a very efficient algorithm for image indexing.
This paper presents a video indexing and representation tool for sequences which contain moving persons, using a model-based dynamic scene analysis. A scenario, describing the sequence in terms of basic events, is pro...
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ISBN:
(纸本)081941767X
This paper presents a video indexing and representation tool for sequences which contain moving persons, using a model-based dynamic scene analysis. A scenario, describing the sequence in terms of basic events, is proposed. These events constitute a first level of annotation and are used to build a visual representation of the sequence called Object Based video Icon. Experiments are carried out and a prototype system is described.
The usefulness of a collection of scanned graphical documents can be measured by the facilities available for their retrieval. We present an approach for indexing a collection of line drawings automatically. The index...
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ISBN:
(纸本)081941767X
The usefulness of a collection of scanned graphical documents can be measured by the facilities available for their retrieval. We present an approach for indexing a collection of line drawings automatically. The indexing is based on the textual and graphical content of the drawings. This approach has been developed to facilitate `retrieval by example' in heterogeneous collections of graphical documents. No a priori knowledge about the application domain is assumed. Starting with a raster image, candidate character patterns and graphical primitives (i.e., line segments and arcs) are extracted. Candidate character patterns are classified by an OCR method and grouped into word hypotheses. Graphical features of various types are computed from groupings of graphical primitives (e.g., sequences of adjacent lines, pairs of parallel lines). retrieval occurs with a weighted information retrieval system. Each document of the collection and each query are described with a set of indexing features with their corresponding weights. The weight of an indexing feature reflects the descriptive nature of the feature and is computed from the number of occurrences of the indexing feature in the document (feature frequency ff) and the number of documents containing the indexing feature (document frequency df).
In order to retrieve a set of intended images from a huge image archive, human beings think of special contents with respect to the searched scene, like a countryside or a technical drawing. Therefore, in general it i...
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ISBN:
(纸本)081941767X
In order to retrieve a set of intended images from a huge image archive, human beings think of special contents with respect to the searched scene, like a countryside or a technical drawing. Therefore, in general it is harder to retrieve images by using a syntactical feature- based language than a language which offers the selection of examples concerning color, texture, and contour in combination with natural language concepts. This motivation leads to a content-based image analysis and goes on to a content-based storage and retrieval of images. Furthermore, it is unreasonable for any human being to make the content description for thousands of images manually. From this point of view, the project IRIS (imageretrieval for information systems) combines well-known methods and techniques in computer vision and AI in a new way to generate content descriptions of images in a textual form automatically. IRIS retrieves the images by means of text retrieval realized by the SearchManager/6000. The textual description is generated by four sub-steps: feature extraction like colors, textures, and contours, segmentation, and interpretation of part-whole relations. The system is implemented on IBM RS/6000 using AIX. It has already been tested with 350 images.
Searching in imagedatabases using image content has made the transition from the laboratory to consumer software. Storm Software is a pioneer in bringing these techniques to shrink-wrapped software applications, and ...
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ISBN:
(纸本)081941767X
Searching in imagedatabases using image content has made the transition from the laboratory to consumer software. Storm Software is a pioneer in bringing these techniques to shrink-wrapped software applications, and this presentation describes some of the methods we use in our products and some of the experiences we have had in bringing this new technology to consumers. We describe the scope of the problem we are trying to solve as well as some of the algorithms and interfaces we used. We also describe some of the rationales (based on theory as well as on user testing) we had for the various design decisions we made. Finally, we describe some of the challenges and opportunities we see ahead. Descriptions and screen shots of two software products implementing image searching (EasyPhoto and Apple PhotoFlash) are provided. Both products were developed by Storm Software.
This paper describes the extended model for information retrieval (EMIR) designed for complex information description and retrieval and particularly well suited for image modeling. A main object in the proposed model ...
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ISBN:
(纸本)081941767X
This paper describes the extended model for information retrieval (EMIR) designed for complex information description and retrieval and particularly well suited for image modeling. A main object in the proposed model has a three parts specification: a description that is a list of attributes;a composition that is a list of component objects;and a topology that is a list of semantic relationships between component objects, expressing more semantic aspects of the main object structure. The model is well suited for image modeling for two complementary reasons. On one hand, it can distinguish between an object structure and its contents. This is achieved by relaxing the class-object classical instantiation link;thus allowing objects to have individual non categorized contents rather than those predicted in their classes. On the other hand, images have typically very different individual contents, and, therefore, cannot be easily modeled within a structured database model such as the relational model. The query language is organized according to the three-part organization of the model. A simple query has three parts: description, being some constraints on some attributes values;composition, being a set of sub-queries on the composition part of objects;topology, being the specification of special required links on the results of composition sub-queries.
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