73 results about "Goal object" patented technology

A system and method for automatic data mapping of a source object to a target object. Field maps can be automatically determined from the source and target objects, database platform, ETL maps, user-defined and data conversion rules, default values, or other pre-defined parameters. Where a change occurs in the source or target data structure, the present invention ensures proper mapping between the source and target data structures occurs, thus reducing the burden of exception handling on the user and preventing oversight in correcting improper mapping. The present invention can also be used by a compiler to generate SQL steps during compile-time processes to design field maps that can be stored as an application class.

The present invention relates generally to computers and computer databases, and more specifically, to a method of and system for converting between Object-oriented classes and markup languages. One aspect of the invention is broadly defined as a method of converting data from a markup language format to an Object model, comprising the steps of: identifying an input markup language document, a destination Object and a markup schema; determining mappings between the input markup language document and the destination Object, including an indication of position for elements having the same name in the input markup language document; traversing the input markup language document; and generating corresponding software Objects with consideration for the position indication.

Techniques for aiding user input with a graphical user interface (GUI) are disclosed. A target object among various command regions of the GUI is predicted, e.g., substantially before the cursor reaches any of the regions. The command region corresponding to the predicted target object is enlarged to facilitate user selection of the predicted target object. Enlarging the predicted target object may cause the target object to overlap and/or occlude nearby command regions. After a first target object is predicted, the prediction may be changed based on updated cursor movements. By using predictive target enlargement, users are given early visual feedback about the target, and are given a larger target to acquire, thereby allowing them to be faster and less precise (their mouse direction can wander) yet still acquire their desired result.

The present invention relates generally to computers and computer databases, and more specifically, to a method of and system for converting between Object-oriented classes and markup languages. One aspect of the invention is broadly defined as a method for converting data from a markup language format to an Object model, comprising the steps of: identifying an input markup language code, a destination Object and a markup schema; determining mappings between the schema and the destination Object, including identification of namespaces associated with elements of the input markup language document; traversing the input markup language document; and instantiating corresponding software Objects with consideration for the namespace.

The invention provides an augmented reality (AR) and virtual reality (VR) combined medical training system. Three-dimensional (3D) images of operation appliances used by operation target objects and training personnel are acquired through a 3D image acquisition module, operation motion of the training personnel is captured in real time through a motion capture module, correction information and guidance information are output through a central processor, an AR or VR model comprising the 3D images acquired by the 3D image acquisition module, the guidance information and the correction information is established, and the training personnel obtains the status of the operation target objects and the operation appliances used by the operation target objects, the guidance information and the correction information in real time through an AR interaction module, such that medical training is enabled to be more realistic and vivid, the medical training period is shortened, and the medical training cost is decreased.

The invention is directed to a system and method of observing actions performed on a computer and generating a timeline that includes timeline entries corresponding to the observed actions. During a computer session, the invention searches the timeline and other locations for objects that relate to target objects that are accessed by users and/or presented to users. The search produces search result objects associated with the target objects. The search result objects may be used to conduct additional searches in order to provide more complete search results.

A semantic-based searching apparatus and method which can search for desired information from various types of media using associative properties of search target objects are provided. The semantic-based searching apparatus stores an associative search structure that previously stores a semantic index. The associative search structure is to obtain a final search object corresponding to an input search query. The semantic index configuration includes feature metadata used to identify a specific object, semantic entity metadata to indicate semantic entities corresponding to the feature metadata, and semantic relation metadata to indicate a relation between the semantic entities. The semantic-based searching apparatus uses semantic metadata stored in conformity with the semantic index configuration, the semantic index, and the associative search structure to generate a search result corresponding to the input search query.

The invention discloses a target tracking method based on spatio-temporal feature fusion learning, and relates to the technical field of computer vision and pattern recognition. The method comprises the steps that firstly, a space-time feature fusion learning network is constructed, space-time features comprise time sequence features and space features, and the time sequence features are extractedin the mode that Alexnet and a time recurrent neural network are combined; Wherein the spatial features are divided into target object spatial transformation features and background spatial features,and YOLOv3 and Alexnet extraction is adopted respectively. In the initial training process of the network, a training data set and a random gradient descent method are used for training the space-time feature fusion learning network, and after training is completed, the network can obtain the initial capacity for positioning the target object. The image sequence to be tracked is input into the network for forward processing, the network outputs the position and confidence of the target object bounding box, the confidence decides whether the network performs online learning or not, and the position of the bounding box realizes positioning of the target object, so that tracking of the target object is realized.

A method for controlling a portable device is disclosed. The method includes displaying a plurality of augmented reality (AR) images, detecting a gaze of a user, determining a target object based on the gaze of the user, identifying an associated AR image that is associated with the target object and a non-associated AR image that is not associated with the target object from the plural AR images, and maintaining display of the associated AR image and terminating display of the non-associated AR image when the target object is a moving object.

One embodiment of the present invention provides a system that facilitates identifying objects rendered on a graphic user interface (GUI) in a non-markup-language-presented software application. During operation, the system receives a non-markup-language-presented application at a computer. The system first selects a set of attributes that uniquely distinguish a target GUI object. The system then identifies a set of target GUI objects in the application, wherein a respective GUI object is not represented in a markup language in the received application. Next, the system represents the target GUI objects in the application with a markup-language-based structure, wherein each target GUI object is associated with a corresponding markup-language node in the structure.

The present invention relates generally to computers and computer databases, and more specifically, to a method of and system for converting between Object-oriented classes and markup languages. One aspect of the invention is broadly defined as a method for converting data from a markup language format to an Object model, comprising the steps of: identifying an input markup language code, a destination Object and a markup schema; determining mappings between the markup schema and the destination Object, distinguishing between data elements and organizational elements of the input markup language code; traversing the input markup language code, following paths in accordance with whether the mappings are data or organizational; and instantiating corresponding software Objects.

A computer-implemented method of tracking a target object in an object recognition system includes acquiring a plurality of images with a camera and simultaneously tracking the target object and dynamically building online map data from the plurality of images. Tracking of the target object is based on the online map data and the offline map data. In one aspect, tracking the target object includes enabling only one of the online map data and offline map data for tracking based on whether tracking is successful. In another aspect, tracking the target object includes fusing the online map data with the offline map data to generate a fused online model.

A method is provided for interacting with the graphical model is provided. At least one of the plurality of views of the graphical model is parsed to create an intermediate representation. An interactive overlay is displayed using the display device. User interacts with the destination object based on an input instruction via the interactive overlay and modifies the destination object using the input instruction, the modifying allows the destination object to perform a modified operation when the model is executed. The graphical model includes execution semantics and a destination object, where the destination object is influenced by the execution semantics. The graphical model is rendered on a display device based on a selected view.

A multiple object tracking system has a system controller with a placement block placing target objects and distractor objects within a 3D display space upon a representation of a solid ground, an assignment block assigning respective trajectories for movement of each of the objects, and an animation block defining an animated sequence of images showing the ground and the objects following the respective trajectories. A visual display presents images to a user including the animated sequence of images and a ground representation. A manual input device is adapted to respond to manual input from the user to select objects believed to be the target objects after presentation of the animated sequence. Preferably, the animation block incorporates a plurality of 3D cues applied to each of the objects, such as 3D perspective, parallax, 3D illumination, binocular disparity, and differing occlusion.

The embodiment of the invention discloses a target object assessment and evaluation method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining an initialscore set of a target object, wherein the target object is an object to be evaluated and comprehensively scored, and the initial score set comprises initial scores of a plurality of index parametersof the target object; obtaining an objective score set of the target object through a first preset rule, wherein the objective score set comprises objective scores of a plurality of index parameters of the target object, and the first preset rule is a calculation rule representing a mapping relationship between the initial score and the objective score; and calculating a comprehensive score of thetarget object according to the objective score set. The target object to be evaluated is scored objectively and fairly, deviation of subjective scoring caused by subjective factors is corrected, thewhole process is automatically completed through the computer device, the labor cost is greatly reduced, the evaluation efficiency of the target object is improved, and meanwhile the evaluation resultis more objective and accurate.

The invention provides a media resource recommendation method and a multi-target fusion model training method and device, belongs to the technical field of machine learning, and can be applied to various scenes such as cloud technology, artificial intelligence and intelligent traffic. The method comprises the steps of determining business target estimation information based on object features of a target object, resource features of media resources and associated features; determining object type information based on the object features; determining recommendation information of the media resources based on the business target estimation information and the object type information; and recommending the media resource to the target object in response to the condition that the recommendation information meets the recommendation condition. According to the technical scheme, the prediction effects of the business targets can be fused on the basis of the probability that the objects belong to the object types, so that the fusion modes of the prediction effects of the objects and the business targets of different object types are different, the accuracy of the fusion result is improved, and the problem of'tradeoff 'can be effectively solved.