Topic
Object (computer science)
About: Object (computer science) is a research topic. Over the lifetime, 106024 publications have been published within this topic receiving 1360115 citations. The topic is also known as: obj & Rq.
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01 Sep 1997TL;DR: This paper provides an overview of these aspects of the Lore system, as well as other novel features such as dynamic structural summaries and seamless access to data from external sources.
Abstract: Lore (for Lightweight Object Repository) is a DBMS designed specifically for managing semistructured information. Implementing Lore has required rethinking all aspects of a DBMS, including storage management, indexing, query processing and optimization, and user interfaces. This paper provides an overview of these aspects of the Lore system, as well as other novel features such as dynamic structural summaries and seamless access to data from external sources.
692 citations
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15 Aug 1994TL;DR: In this paper, an apparatus and method enables a user to control the selection of electronic multimedia services to be provided to the user by one or more servers over a communication medium, including a scanner for reading marks on an object and for communicating a request signal, having an object code representing the read marks, to a user interface.
Abstract: An apparatus and method enables a user to control the selection of electronic multimedia services to be provided to the user by one or more servers over a communication medium. The apparatus includes a scanner for reading marks on an object and for communicating a request signal, having an object code representing the read marks, to a user interface. The interface receives the request signal and transmits to the servers a request command including an interface identification code and the object code which is used to select the desired electronic multimedia service. The servers identify the selected electronic multimedia service using the object code. The interface then enables the selected electronic multimedia service transmitted from the servers to be received by the user's receiver.
681 citations
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13 Jun 2010TL;DR: A new random field model is proposed to encode the mutual context of objects and human poses in human-object interaction activities and it is shown that this mutual context model significantly outperforms state-of-the-art in detecting very difficult objects andhuman poses.
Abstract: Detecting objects in cluttered scenes and estimating articulated human body parts are two challenging problems in computer vision. The difficulty is particularly pronounced in activities involving human-object interactions (e.g. playing tennis), where the relevant object tends to be small or only partially visible, and the human body parts are often self-occluded. We observe, however, that objects and human poses can serve as mutual context to each other – recognizing one facilitates the recognition of the other. In this paper we propose a new random field model to encode the mutual context of objects and human poses in human-object interaction activities. We then cast the model learning task as a structure learning problem, of which the structural connectivity between the object, the overall human pose, and different body parts are estimated through a structure search approach, and the parameters of the model are estimated by a new max-margin algorithm. On a sports data set of six classes of human-object interactions [12], we show that our mutual context model significantly outperforms state-of-the-art in detecting very difficult objects and human poses.
673 citations
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01 Jan 1983TL;DR: Traditional techniques for this purpose, developed in cluster analysis and numerical taxonomy, are often inadequate because they arrange objects into classes solely on the basis of a numerical measure of object similarity.
Abstract: An important form of learning from observation is constructing a classification of given objects or situations. Traditional techniques for this purpose, developed in cluster analysis and numerical taxonomy, are often inadequate because they arrange objects into classes solely on the basis of a numerical measure of object similarity. Such a measure is a function only of compared objects and does not take into consideration any global properties or concepts characterizing object classes. Consequently, the obtained classes may have no simple conceptual description and may be difficult to interpret.
668 citations
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16 Jul 2003
TL;DR: A computer data processing system including a central processing unit configured with a novel integrated computer control software system for the management of data objects including dynamic and automatic organization, linking, finding, cross-referencing, viewing and retrieval of multiple objects regardless of nature or source.
Abstract: A computer data processing system including a central processing unit configured with a novel integrated computer control software system for the management of data objects including dynamic and automatic organization, linking, finding, cross-referencing, viewing and retrieval of multiple objects regardless of nature or source. The inventive system provides underlying component architecture having an object-oriented database structure and a metadata database structure which is unique in storing only one instance of each object while linking the object to multiple collections and domains by unique metadata links for the grouping into and retrieval from any of the collections. The system employs configurable, extensible attribute/properties of data objects in metadata format, and a truly user-friendly configurable interface that facilitates faster, more unified, comprehensive, useful and meaningful information management. Additional features include a sticky path object hierarchy viewing system, key phrase linking, viewing by reference, and drag-and-drop relationship link creation.
667 citations