Abstract: A system for providing augmented reality detects foreground occluders in an image of a video stream. One or more virtual objects are then rendered appropriately with respect to the occluders. Location information associated with the image is used to retrieve a three dimensional representation of the location where the image was taken. Features that are expected to appear in the image based on the three dimensional location but that cannot be located are used to determine regions of the image that are likely to include foreground occluders. Pixels in these regions are used to train a color model that classifies pixels as either part of the background of the image or part of one or more foreground occluders. The pixels in the image are classified using the model, and one or more virtual objects are rendered so that they appear behind any foreground occluders.

Abstract: An efficient manner of performing an M-out-of-N partial matching search of indexed documents (e.g., web pages) is provided herein. More particularly, indexed words are arranged into a global location space (GLS), providing for respective occurrences of words in indexed documents being searched to have continuous locations on a one-dimensional GLS. Documents within the GLS are separated by end of document word marking boundaries between consecutive documents. The query words are then separated into an active set, comprising the left-most query words, and a non-active set. A partial matching operator transverses the GLS, applying active geometric constraints, in a sequential manner, to words in the active set. This causes shifting of the active set along the GLS to comprise M left-most query words. If a document satisfies constraints associated with M words in an active set, the document comprises at least M-out-of-N words.

Abstract: A system and method for providing an augmented reality environment in which the environmental mapping process is decoupled from the localization processes performed by one or more mobile devices is described. In some embodiments, an augmented reality system includes a mapping system with independent sensing devices for mapping a particular real-world environment and one or more mobile devices. Each of the one or more mobile devices utilizes a separate asynchronous computing pipeline for localizing the mobile device and rendering virtual objects from a point of view of the mobile device. This distributed approach provides an efficient way for supporting mapping and localization processes for a large number of mobile devices, which are typically constrained by form factor and battery life limitations.

Abstract: An image may be received, a portion of which corresponds to a surface of an object, such as a book, a CD, a DVD, a wine bottle, etc. The portion of the image that corresponds to the surface of the object is located. The portion of the image is compared with previously stored images of surfaces of objects to identify the object. A record of the object is created and added to a library. The record of the object may comprise the image of the object, the portion of the image which corresponds to the surface of the object, and/or the received image itself. The record may comprise an indicator of a location of the object.

Abstract: Images in a database or collection of images are each divided into multiple partitions with each partition corresponding to an area of an image. The partitions in an image may overlap with each other. Min-hash sketches are generated for each of the partitions and stored with the images. A user may submit an image and request that an image that is a partial match for the submitted image be located in the image collection. The submitted image is similarly divided into partitions and min-hash sketches are generated from the partitions. The min-hash sketches are compared with the stored min-hash sketches for matches, and images having partitions whose sketches are matches are returned as partial matching images.

Abstract: Techniques for defocusing queries over big datasets and dynamic datasets are provided to broaden search results and incorporate all potentially relevant data and avoid overly narrowing queries. An analytic component can receive queries directed at one region of a dataset and analyze the queries to generate inferences about the queries. The queries can then be defocused by a defocusing component and incorporate a larger dataset than originally searched to broaden the queries. The larger dataset can incorporate all, or a part of the original dataset and can also be disparate from the original dataset. Clusters of queries can also be merged and unified to deal with ‘local minima’ issues and broaden the understanding of the dataset. In other embodiments, dynamic data can be monitored and changes tracked, to ensure that all portions of the dataset are being searched by the queries.

Abstract: Data management techniques are provided for handling of big data. A data management process can account for attributes of data by analyzing or interpreting the data, assigning intervals to the attributes based on the data, and effectuating policies, based on the attributes and intervals, that facilitate data management. In addition, the data management process can determine relations among data in a data collection and generate and store approximate results concerning the data based on the attributes, intervals, and the policies.

Abstract: Techniques for efficiently performing queries are provided. A search component can receive a request for information based on data, and a management component can determine a degree of accuracy requested for the information. In turn, the search component can render the information based on the degree of accuracy requested. In an aspect, the search generates a query configured to determine the first information, and the management component instructs the search component to perform the query to a level of completion less than full completion when the degree of accuracy requested is below a predetermined threshold to cause the search component to render an estimation of the first information. In another aspect, a tracking component can track information associated with multiple query requests and an analysis determine and employ a related aspect of the tracked information to a new query request to determine an answer for a the new query request.

Abstract: Techniques for defocusing queries over big datasets and dynamic datasets are provided to broaden search results and incorporate all potentially relevant data and avoid overly narrowing queries. An analytic component can receive queries directed at one region of a dataset and analyze the queries to generate inferences about the queries. The queries can then be defocused by a defocusing component and incorporate a larger dataset than originally searched to broaden the queries. The larger dataset can incorporate all, or a part of the original dataset and can also be disparate from the original dataset. Clusters of queries can also be merged and unified to deal with ‘local minima’ issues and broaden the understanding of the dataset. In other embodiments, dynamic data can be monitored and changes tracked, to ensure that all portions of the dataset are being searched by the queries.

Abstract: The subject disclosure relates to using structured query language constructs in non-structured query language domains. For example, through mathematical and logical transformation of concepts from a key, value pair domain associated with structured query language data structures to graphical-related data structures, the value originating in the structured query language domain can be modified for use in non-structured query language domains. This can open up options in analytics and can solve some of the problems associated with liner algebra.

Abstract: Computations are performed on shared datasets in a distributed computing cluster using aggressive speculation and a distributed runtime that executes code transactionally. Speculative transactions are conducted with currently available data on the assumption that no dependencies exist that will render the input data invalid. For those specific instances where this assumption is found to be incorrect—that the input data did indeed have a dependency (thereby impacting the correctness of the speculated transaction)—the speculated transaction is aborted and its results (and all transactions that relied on its results) are rolled-back accordingly for re-computation using updated input data. In operation, shared state data is read and written using only the system's data access API which ensures that computations can be rolled-back when conflicts stemming from later-determined dependencies are detected.

Abstract: Methods are disclosed for finding images from a large corpus of images that at least partially match a query image. The present method makes use of feature detectors to bundle features into local groups or bundles. These bundled features are repeatable and much more discriminative than an individual SIFT feature. Equally importantly, the bundled features provide a flexible representation that allows simple and robust geometric constraints to be efficiently enforced when querying the index.

Abstract: A system for providing augmented reality detects foreground occluders in an image of a video stream. One or more virtual objects are then rendered appropriately with respect to the occluders. Location information associated with the image is used to retrieve a three dimensional representation of the location where the image was taken. Features that are expected to appear in the image based on the three dimensional location but that cannot be located are used to determine regions of the image that are likely to include foreground occluders. Pixels in these regions are used to train a color model that classifies pixels as either part of the background of the image or part of one or more foreground occluders. The pixels in the image are classified using the model, and one or more virtual objects are rendered so that they appear behind any foreground occluders.

Abstract: A job scheduler may schedule concurrent distributed jobs in a computer cluster by assigning tasks from the running jobs to compute nodes while balancing fairness with efficiency. Determining which tasks to assign to the compute nodes may be performed using a network flow graph. The weights on at least some of the edges of the graph encode data locality, and the capacities provide constraints that ensure fairness. A min-cost flow technique may be used to perform an assignment of the tasks represented by the network flow graph. Thus, online task scheduling with locality may be mapped onto a network flow graph, which in turn may be used to determine a scheduling assignment using min-cost flow techniques. The costs may encode data locality, fairness, and starvation-freedom.

Abstract: A system and method for providing an augmented reality environment in which the environmental mapping process is decoupled from the localization processes performed by one or more mobile devices is described. In some embodiments, an augmented reality system includes a mapping system with independent sensing devices for mapping a particular real-world environment and one or more mobile devices. Each of the one or more mobile devices utilizes a separate asynchronous computing pipeline for localizing the mobile device and rendering virtual objects from a point of view of the mobile device. This distributed approach provides an efficient way for supporting mapping and localization processes for a large number of mobile devices, which are typically constrained by form factor and battery life limitations.

Abstract: Methods are disclosed for finding images from a large corpus of images that at least partially match a query image. The present method makes use of feature detectors to bundle features into local groups or bundles. These bundled features are repeatable and much more discriminative than an individual SIFT feature. Equally importantly, the bundled features provide a flexible representation that allows simple and robust geometric constraints to be efficiently enforced when querying the index.

Abstract: General-purpose distributed data-parallel computing using high-level computing languages is described. Data parallel portions of a sequential program written in a high-level language are automatically translated into a distributed execution plan. Map and reduction computations are automatically added to the plan. Patterns in the sequential program can be automatically identified to trigger map and reduction processing. Direct invocation of map and reduction processing is also provided. One or more portions of the reduce computation are pushed to the map stage and dynamic aggregation is inserted when possible. The system automatically identifies opportunities for partial reductions and aggregation, but also provides a set of extensions in a high-level computing language for the generation and optimization of the distributed execution plan. The extensions include annotations to declare functions suitable for these optimizations.

Abstract: Image search results are obtained by providing weights to visual features to emphasize features corresponding to objects of interest while simultaneously deemphasizing irrelevant or inconsistent features that lead to poor search results. In order to minimize the impact of visual features that are unreliable or irrelevant with respect to the objects of interest in the image, context-dependent weights are provided to detect visual features such that those visual features pertaining to the objects of interest are more heavily weighted than those visual features that pertain to irrelevant or unreliable portions of the image. Visual features may be weighted for images in a searchable database. Training data may be obtained and used in weighting visual features in a query image and, alternatively, in searchable database images.

Abstract: General-purpose distributed data-parallel computing using high-level computing languages is described. Data parallel portions of a sequential program that is written by a developer in a high-level language are automatically translated into a distributed execution plan. A set of extensions to a sequential high-level computing language are provided to support distributed parallel computations and to facilitate generation and optimization of distributed execution plans. The extensions are fully integrated with the programming language, thereby enabling developers to write sequential language programs using known constructs while providing the ability to invoke the extensions to enable better generation and optimization of the execution plan for a distributed computing environment.

Abstract: A general purpose high-performance distributed execution engine can be used by developers to deploy large-scale distributed applications. To allow developers to easily make use of the distributed execution engine, a graph building language is proposed that enables developers to efficiently create graphs (e.g., direct acyclic graphs) that describe the subprograms to be executed and the flow of data between them. A job manager (or other appropriate entity) reads the description of the graph created with the graph building language, builds the graph based on that description, and intelligently distributes the subprograms according to the graph so that system resources are used efficiently. In one embodiment, the graph building language (and, thus, the description of the graph) includes syntax for replication, pointwise connect, cross connect and merge.