619 results about "Object Class" patented technology

A CORBA Gateway between CORBA-based applications and an enterprise manager may be configurable to manage various networked objects, such as printers, scanners, copiers, telephone systems, cell phones, phone systems, faxes, routers, switches, etc., which may be interconnected via networks. Various embodiments of the CORBA Gateway may include an Event Gateway which manages object events. The CORBA Event Gateway is designed to leverage existing Event Distribution Server (EDS) sinks to provide EDS filtering functionality and EDS object level access control functionality. The approach leverages existing EDS solutions by providing a common sink for all events / notifications and using a unique Event Port Registry to manage the subscriptions of various TMN clients that subscribe for such events / notifications. Generally, the approach described provides the capability to filter events according to criteria presented by client event subscriptions. In one embodiment, the events may be filtered to enforce policy-based access control on TMN events / notifications, determining which CORBA client applications have access to which events. The filtering of events at the sink based upon client subscriptions decreases unnecessary network traffic in that events may be “pushed” to the client, rather than delivered upon client request. In addition, the approach may provide easy-to-use IDL APIs that allow CORBA clients to directly subscribe / unsubscribe to events based on criteria such as object class, object instance, and event type.

A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and / or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

A computer-implemented method executed by at least one processor for training fast models for real-time object detection with knowledge transfer is presented. The method includes employing a Faster Region-based Convolutional Neural Network (R-CNN) as an objection detection framework for performing the real-time object detection, inputting a plurality of images into the Faster R-CNN, and training the Faster R-CNN by learning a student model from a teacher model by employing a weighted cross-entropy loss layer for classification accounting for an imbalance between background classes and object classes, employing a boundary loss layer to enable transfer of knowledge of bounding box regression from the teacher model to the student model, and employing a confidence-weighted binary activation loss layer to train intermediate layers of the student model to achieve similar distribution of neurons as achieved by the teacher model.

An automated image processing system and method are provided for class-based segmentation of a digital image. The method includes extracting a plurality of patches of an input image. For each patch, at least one feature is extracted. The feature may be a high level feature which is derived from the application of a generative model to a representation of low level feature(s) of the patch. For each patch, and for at least one object class from a set of object classes, a relevance score for the patch, based on the at least one feature, is computed. For at least some or all of the pixels of the image, a relevance score for the at least one object class based on the patch scores is computed. An object class is assigned to each of the pixels based on the computed relevance score for the at least one object class, allowing the image to be segmented and the segments labeled, based on object class.

A method and system for persisting an object in a relational database schema by creating a new relational table at application program run-time for each class of objects to be persisted. The method may generate a schema map object for each class of objects to be persisted. The schema map object may be generated in response to the first transaction in which an object of a certain class is to be persisted and remains in memory for persisting, querying, restoring or deleting objects of that class. The schema map object determines the fields of each class of objects to be persisted, defines one or more columns in the table in accordance with the data types of the fields, and controls the passing of data between the table and the object fields.

A technique for easily making modifications to a graphical user interface (GUI). XML files each containing different rules for making a tree display are easily written by code developers. The files are merged into a document object model (DOM) stored in memory. The GUI display presentation can thus be easily updated by the code developers by modifying the rules stored in the DOM by merging additional XML files containing rule additions, deletions and / or modifications into the DOM. The DOM is parsed for certain object classes for which object instances are needed. The object instances having certain display properties are retrieved from the system or network with which the GUI is operative and are combined with certain display attributes or display rules stored in the DOM. The object instances including their display properties and attributes are returned to the GUI to be displayed on the terminal screen in accordance therewith.

An online system for permitting users in a data network to manage inventories of their collectibles (including antiques) includes a database of collectibles, user inventory files, user information files, a database of needed items and items available for sale, and a server-based task for managing and searching the database of needed items and items available for sale. The database of collectibles includes object classes indexed by primary classes and subclasses, and user inventory files storing inventories of instances of the object classes, including instances that each user has, instances that each user would like to sell, and instances that each user would like to buy. Users may access their respective inventories by inspecting, editing, and adding the instances to the user inventories; obtaining valuations of instances in their inventories; and insuring instances in their inventories. The server-based task finds buy-sell opportunities between the users when one user has an instance of at least one object class that said one user would like to buy and another user has an instance of said at least one object class that said another user would like to sell.

A method includes receiving or capturing a digital image using a mobile device, and using a processor of the mobile device to: determine whether an object depicted in the digital image belongs to a particular object class among a plurality of object classes; determine one or more object features of the object based at least in part on the particular object class at least partially in response to determining the object belongs to the particular object class; build or select an extraction model based at least in part on the one or more determined object features; and extract data from the digital image using the extraction model. The extraction model excludes, and / or the extraction process does not utilize, optical character recognition (OCR) techniques. Related systems and computer program products are also disclosed.

A camera system comprises an image capturing device and an object classification module connected to the image capturing device. The image capturing device has a field of view and produces image data representing an image of the field of view. The object classification module is operable to determine whether or not an object in an image is a member of an object class. The object classification module includes N decision steps configured in a cascade configuration, wherein at least one of the N decision steps is operable to (a) accept an object as a member of the object class, (b) reject an object as a member of the object class, and (c) call on a next step to determine whether or not an object is a member of the object class.

A method for training a system for detecting multi-class objects in an image or a video sequence is described. A common ensemble of weak classifiers for a set of object classes is identified. For each object class, a separate weighting scheme is adapted for the ensemble of weak classifiers. A method for detecting objects of multiple classes in an image or a video sequence is also disclosed. Each class is assigned a detector that is implemented by a weighted combination of weak classifiers such that all of the detectors are based on a common ensemble of weak classifiers. Then weights are individually set for each class.

A framework for use with object-oriented programming systems provides a software build system that detects modules that make up a software product, examines each module to determine if it is up-to-date, and automatically updates any modules that require processing. The framework includes a software object of a class called "Product" that comprises a software product to be processed and built. An instance of the Product is comprised of multiple software build objects, each of which is called "Object". Each Object in turn contains four objects that are a kind of object class called BldSrc (Build Source). The BldSrc objects specify a different aspect of the software product and desired processing. Each of the software build objects in a Product's Object list is examined to determine if all four of the BldSrc objects is current. If any one of the software build objects is not current, the Object is re-built. If all four objects are current, the re-building step is skipped. In this way, each of the software build Objects making up a Product is automatically examined and processed, and the Product is produced.

Systems and methods for processing an image to determine whether segments of the image belong to an object class are disclosed. In one embodiment, the method comprises receiving digitized data representing an image, the image data comprising a plurality of pixels, segmenting the pixel data into segments at a plurality of scale levels, determining feature vectors of the segments at the plurality of scale levels, the feature vectors comprising one or more measures of visual perception of the segments, determining one or more similarities, each similarity determined by comparing two or more feature vectors, determining, for each of a first subset of the segments, a first measure of probability that the segments is a member of an object class, determining probability factors based on the determined first measures of probability and similarity factors based on the determined similarities, and performing factor graph analysis to determine a second measure of probability for each of a second subset of the segments based on the probability factors and similarity factors.

A Web Interface and Method for Accessing Directory Information is disclosed. A Web Interface for Accessing Directory Information comprises a request mapper that links directory data to a template file in response to a directory request, and a friendly name mapper that correlates an abbreviated name to a non-abbreviated name. The abbreviated name refers to at least one entry of said directory data. A method for accessing directory information in accordance with the invention comprises the following steps: (1) receiving a request for directory data; (2) determining whether the request is a distinguished name request, wherein the distinguished name request is a request for a distinguished name; (3) in response to a determination that the request is not a distinguished name request, retrieving a directory resource corresponding to the request; (4) in response to a determination that the request is a distinguished name request, determining whether the distinguished name is mapped; (5) in response to a determination that the distinguished name is not mapped, retrieving an object class of the distinguished name and finding a template using the object class; and (6) in response to a determination that the distinguished name is mapped, finding a template using the distinguished name.

Devices for remotely addressing objects via pointing action are provided with graphical user interfaces. In response to an object being addressed, a computer device and software provide graphical user interfaces which relates to objects being addressed. As different types of objects are addressed, user interfaces provided change in form and function to agree with the type of category of object being addressed at that instant. Devices have position and attitude determining facility in communication with a computer having prerecorded data. The data includes information relating to object types and corresponding graphical user interfaces.

A set of object classes provide a framework supporting user modification of user interface properties. The classes include a properties class which is a template for creation of property objects encapsulating property values and the view attributes (GUI information) required for creating views of the property via a user interface. Property objects provide a single mechanism for representing a particular property, allowing a number of different views to be open on the same property. User interactions with different views of a property via the user interface result in messages being sent to the same property object. If a property value is changed, then the chance is propagated back to all associated applications having views for the object and so view concurrency is automatically achieved.

A method of object detection includes receiving images of an area occupied by at least one object. Image features including wavelet features are extracted from the images. Classification is performed on the image features as a group in at least one common classification algorithm to produce object class confidence data.

A system and method for managing network devices. The framework may provide a suitable system for managed object data type conversions between various data description languages, such as an interface definition language (e.g., OMG IDL) and an abstract syntax notation (e.g., ASN1). This conversion facility may be used in both request and event network traffic, so common libraries may be used. Two separate libraries may be used: a converter framework library and a converter implementation library. The framework library provides a collection classes that may be used by the clients of the converter libraries. Most classes in the converter framework library are handle classes (or wrappers) to the real implementation (or body) classes in the converter implementation library. Framework classes hide the details of the real implementation classes and provide a simple, consistent interface to any data type converter via IDL. The converter implementation library provides the implementation needed by the framework to function properly, and may allow various different mappings to be used easily by implementing them as plug-in modules. The combination of using IDL and generic typing provides an efficient, generic solution to mapping data types across multiple platforms, multiple programming languages, and multiple object classes.

In one embodiment, a method includes receiving a digital image captured by a mobile device; and using a processor of the mobile device: generating a first representation of the digital image, the first representation being characterized by a reduced resolution; generating a first feature vector based on the first representation; comparing the first feature vector to a plurality of reference feature matrices; and classifying an object depicted in the digital image as a member of a particular object class based at least in part on the comparing.

A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and / or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

A method and system for accessing network directory data as uses a Web service as an interface between a directory database and network clients. To support extensibility of the object types in the directory database, directory access methods are defined for a generic object class from which classes for different directory object types are derived. A description of the object classes and database operation methods is provided by the Web service to the client. To access the directory database, the runtime environment of the client is used to create objects on which a requested directory operation method operates according to the proper class definitions of the object types. The request with serialized objects is sent to the Web service, which then uses information provided by the objects in the request to access the directory database to carry out the requested directory operation method.

A server method for converting objects of a first type into objects of a second type, the method comprising: a) identifying one or more object classes of the first type; b) determining instance data based on the classes of the first type; c) introspecting each class of the first type; d) creating an artifact representing a software model; and e) generating one or more converters, each converter being based on the artifact and is configured for receiving the instance data and generating JavaScript code for recreating the instance from the classes as objects of the second type, for display on a browser.

The invention relates to a system and method for recognition, classification and spatial localization of bounded 3D-objects. In particular it relates to a computerized method for recognition, classification and localization of objects. The method comprises generation of a training database based on a large number of training views recorded by a camera or constructed using a CAD representation of an object. Characteristic curves are derived from the training views, and primitives of the curves are detected. Intrinsic and extrinsic descriptors of features are stored in the database together with data about the object class and pose of the view. Finally the recognition takes place in two stages: First the intrinsic descriptors of the recognition view are compared with those of the database. Second, among the best matching features it is explored which features agree mutually in the sense that they suggest the same object class at the same pose.

A method and system is provided for allowing efficient creation of data structures that correspond to data formats specified by content models specified within XML schemas. The data in these data structures is produced as XML documents that conform to those XML schema. Programs written in dynamic programming languages, such as JavaScript, create and instantiate object classes that conform to one or more pre-existing XML schemas. These object classes provide an application program interface (API) for application programs to manipulate data via exposed data structures and methods. Application programs are able to access exposed data structures through conventional programming methods. After the application program has completed manipulation of data within the instantiated data classes, the data is then produced as an XML document that conforms to the XML schema.

Methods, apparatus, and business techniques are disclosed for use in distributed communication systems comprising a plurality of communication protocols. In one embodiment a first air interface is used to initiate communication between a wireless client and a remote server at least partially using a first wireless access point. The server sends the wireless client a stub of a distributed object. The stub is used to instantiate an object class. The object class defines an interface that the remote client can use to communicate with the remote server using an upper layer interface. The distributed object stub also provides an implementation of a software radio configuration for a set of lower protocol layers in a second air interface. The wireless client can thereby communicate with a second wireless access point using said second air interface protocol. Exemplary embodiments of the present invention are disclosed that focus on toll-tag and electronic-commerce related highway systems, distributed federated wireless access systems, and wide area wireless system capacity augmentation.

A method, computer program product, and data processing system for exchanging information regarding software source code among a team of developers is disclosed. In a preferred embodiment of the present invention, a developer associates commentary with a particular code feature, such as a function or object class. A list of intended recipients or readers of the commentary is obtained from the developer. Additional settings regarding such things as an expiration date for the commentary are also obtained from the developer. The source code with associated commentary is then made available to the intended readers. If desired, the source code with associated commentary may be transmitted the intended recipients via e-mail or an “instant message” or other form of notification can be transmitted to the intended recipients to notify them of the commentary to be read.

A method for determining an accident risk of a first object with at least one second object is proposed, a collision probability and a hazard probability of the at least one second object being determined in a predefined region around the first object, the collision probability and the hazard probability being determined as a function of motions and object classes of the first and the at least one second object. The accident risk is then determined as a function of the collision probability and the hazard probability.

A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and / or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

The invention supports the management of financial assets such as accounts receivable or mortgages. The invention provides a facility for a user to define rules to segregate assets into pools, define purchasing rules, capture real time information regarding transactions, reconcile payments and produce exception reports, define access rules for individual users to see information relating to pools of assets and individual assets within a pool, and provide customized reports and access to asset details over a network. Abstract representations of financial assets are used to obtain instances of defined financial-asset object classes to define pools of financial assets with common abstract characteristics. The invention uses a tree structured representation of asset classes for allocation of transactions to tranches and sub-tranches of assets within a pool. A user may define custom tranches and sub-tranches, as well as design pools of assets to an investment rating specification in advance.

Systems and methods for processing an image to determine whether segments of the image belong to an object class are disclosed. In one embodiment, the method comprises receiving digitized data representing an image, the image data comprising a plurality of pixels, segmenting the pixel data into segments at a plurality of scale levels, determining feature vectors of the segments at the plurality of scale levels, the feature vectors comprising one or more measures of visual perception of the segments, determining one or more similarities, each similarity determined by comparing two or more feature vectors, determining, for each of a first subset of the segments, a first measure of probability that the segments is a member of an object class, determining probability factors based on the determined first measures of probability and similarity factors based on the determined similarities, and performing factor graph analysis to determine a second measure of probability for each of a second subset of the segments based on the probability factors and similarity factors.