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.

Process for monitoring a plurality of object types of a plurality of nodes from a management node in a data processing system by distributing configured agents

Abstract: The present invention relates to a process for monitoring a plurality of object types of a plurality of nodes (N1, N2, . . . , Nn) comprising a management node (MN) in an information system. Monitoring is configured and then distributed in a filtered way from the management node (MN) to autonomous agents (SAA), an autonomous agent being installed in each node to be monitored in order, by providing intertype correlation, either to locally process the different object types or all of the objects of a domain called a global object, defined generically, or to feed back information to be displayed to the graphical interface of the management node, each agent comprising a plurality of specific modules (SM1, SM2, . . . , SMn) specific to the different object types or to a particular domain, each specific module measuring static and dynamic parameters particular to the object type it monitors and collecting said measurements, testing conditions on said parameters relative to predefined thresholds and possibly triggering actions associated with said tested conditions, which parameters, conditions and actions can be modified by the user of the management node.

Finding Pictures of Objects in Large Collections of Images

Abstract: Retrieving images from very large collections, using image content as a key, is becoming an important problem. Users prefer to ask for pictures using notions of content that are strongly oriented to the presence of abstractly defined objects. Computer programs that implement these queries automatically are desirable, but are hard to build because conventional object recognition techniques from computer vision cannot recognize very general objects in very general contexts. This paper describes our approach to object recognition, which is structured around a sequence of increasingly specialized grouping activities that assemble coherent regions of image that can be shown to satisfy increasingly stringent constraints. The constraints that are satisfied provide a form of object classification in quite general contexts. This view of recognition is distinguished by: far richer involvement of early visual primitives, including color and texture; hierarchical grouping and learning strategies in the classification process; the ability to deal with rather general objects in uncontrolled configurations and contexts. We illustrate these properties with four case-studies: one demonstrating the use of color and texture descriptors; one showing how trees can be described by fusing texture and geometric properties; one learning scenery concepts using grouped features; and one showing how this view of recognition yields a program that can tell, quite accurately, whether a picture contains naked people or not.

A query algebra for object-oriented databases

Abstract: An algebra that synthesizes relational query concepts with object-oriented databases is defined. The algebra fully supports abstract data types and object identity, while providing associative access to objects. The operations take an abstract view of objects and access typed collections of objects through the public interface defined for the type. The algebra supports access to relationships implied by the structure of the objects, as well as the definition and creation of new relationships between objects. The operations create new objects with unique identities and can use object identity in the manipulation of objects. The support for object identity leads to new definitions for equality of results and operators that can manipulate the identities of objects. >

Means for resolving ambiguities in text based upon character context

Abstract: A method of identifying an object within a set of object candidates includes the steps of: calculating the probability of occurrence of each member of a set of string candidates, wherein each string candidate contains one member of the set of object candidates, the calculating employing formulae using a method of groups and projections; and identifying one of the objects based on the calculated probability.

System and method for implementing proximity or location driven activities

Abstract: A system and associated method that allow particular requests to be executed at some point in the future without specifying the exact time or necessarily a precise location. The execution time of the request is linked to the arrival of a person or object at, or near a geographic destination location. When a person, an object, or a group of persons or objects, arrives at the destination location, or comes close to it, the request to interact will be executed. The proximity threshold can be adjustable or programmable.