Longsand Limited

Open Text Corporation

Aurasma Limited

Micro Focus Lcc

Hewlett-packard Development Company, L.p.

Crowdstrike, Inc.

Autonomy Corporation Ltd

Sean Blanchflower

Timothy Halbert

James Loxam

Simon Hayhurst

Michael Richard Lynch

Brian Cowe

Pashmina Cameron

George Saklatvala

Mahapathy Kadirkamanathan

Stephen Davis

Darren Gallagher

Christopher Ogden

Joel Peter Dockray

Barnaby Wainwright

Tung Jin Chew

Brian Beckett

John Simon Fothergill

Fernando Lucini

Augmented reality presentations are provided at respective electronic devices. A first electronic device receives information relating to modification made to an augmented reality presentation at a second electronic device, and the first electronic device modifies the first augmented reality presentation in response to the information.

Collaborative augmented reality

Embodiments of the present disclosure provide systems and methods for reverse decompression. According to one embodiment of the present disclosure, the method for reverse decompression includes receiving encoded and compressed input data in a form of one or more data blocks and locating an end of block marker for a last block of the one or more data blocks of the input data. The method also includes traversing the input data, bit by bit, in a reverse direction starting from a last bit of the end of block marker of the last block of the one or more data blocks of the input data towards a beginning of the input data, determining if one block of the one or more blocks of the input data can be designated as a valid block, designating the one block as a valid block and decompressing the valid block in a forward direction.

Partial decompression for rapid file or sub-file access

A request to send a file is received. A file type for the file is identified. For example, the file type may a Joint Photographic Experts Group (JPEG) file or a Portable Document Format (PDF) file. In response to receiving the request to send the file and identifying the file type for the file, a format of the file is reordered. Reordering the format of the file is based on an application and/or an application type that will be receiving the file. For example, the application may be an Adobe Acrobat® reader that is receiving a PDF file that has been reordered for more efficient reading.

Optimization of a file format

According to examples, an apparatus may identify a first viewpoint that an entity expressed in a first media file, identify a second viewpoint expressed in a second media file that is attributed to the entity, determine that the second viewpoint is dissimilar to the first viewpoint and in response to the determination that the second viewpoint is dissimilar to the first viewpoint, may output a message.

Entity viewpoint determinations

Identification of augmented features based on a Bayesian analysis of a text document is disclosed. One example is a system including a document processing module, a feature processing module, and a feature generation module. The document processing module receives a text document via a processor. The feature processing module automatically identifies, based on a Bayesian analysis of the text document, a plurality of augmented features in the text document, the plurality of augmented features including at least one of local, sectional, and document-level features of the text document, and extracts, via the processor, the identified plurality of augmented features from the text document. The feature generation module generates, via the processor, a feature representation of the text document based on the extracted plurality of augmented features.

Identifying augmented features based on a bayesian analysis of a text document

In some examples, a system performs language processing of text of an information page to determine whether the text refers to an online resource, and in response to determining that the text refers to the online resource, identify the text as an implicit reference to the online resource. The system derives a link to the online resource based on the implicit reference, the derived link useable in accessing the online resource.

Deriving links to online resources based on implicit references

According to examples, an index of entries may be retrieved, in which each of the entries may correspond to phrases that are analogous to other phrases in content on a network. A plurality of phrases that are similar to the entries in the index may be identified in a content accessed on the apparatus and a determination may be made, based on a user interaction with the accessed content via a user interface, that the user has read a first phrase in the plurality of phrases. The index may be updated to indicate that the user has read the first phrase and, based on the updated index, a second phrase in a subsequently accessed content that is similar to the first phrase may be determined. In addition, the second phrase in the subsequently accessed content may be displayed differently from other displayed phrases in the subsequently accessed content.

Distinguish phrases in displayed content

Examples disclosed herein relate to a person moving in a physical space. In one aspect, a method is disclosed. The method may include obtaining at least two images of a person from at least two cameras directed at a physical space, where the physical space may include a plurality of designated areas. The method may also include obtaining metadata associated with the images, based on the images and the metadata determining within the plurality of designated areas a set of designated areas visited by the person, for each designated area within the set of designated areas, determining an area information, and updating a database based on the set of designated areas and based on at least a portion of the area information associated with each designated area within the set of designate areas.

Updating a behavioral model for a person in a physical space

Techniques associated with three-dimensional object modeling are described in various implementations. In one example implementation, a method may include receiving a plurality of two-dimensional images depicting views of an object to be modeled in three dimensions. The method may also include, processing the plurality of two-dimensional images to generate a three-dimensional representation of the object, and analyzing the three-dimensional representation of the object to determine whether sufficient visual information exists in the plurality of two-dimensional images to generate a three-dimensional model of the object. The method may also include, in response to determining that sufficient visual information does not exist for a portion of the object, identifying the portion of the object to a user.

Three-dimensional object modeling

At least a computer-implemented method and an apparatus for processing an image are described. In examples, numeric values for at least one property of the image are determined. These values are then converted into at least one corresponding text character, said conversion being independent of any text content within the image. This enables a text representation of the image to be generated that contains said plurality of text characters. This text representation may be used to index and search for the image.

Textual representation of an image

Optical character recognition is described in various implementations. In one example implementation, a method may include receiving a plurality of optical character recognition (OCR) outputs provided by a respective plurality of OCR engines, each of the plurality of OCR outputs being representative of text depicted in a portion of an electronic image. The method may also include identifying a document context associated with the electronic image, and generating an output character set by applying a character resolution model to resolve differences among the plurality of OCR outputs. The character resolution model may define a probability of character recognition accuracy for each of the plurality of OCR engines given the identified document context. The method may also include updating the character resolution model to generate an updated character resolution model such that subsequent generating of output character sets are based on the updated character resolution model.

Growing community of inventors

Cambridge, United Kingdom

Sean Blanchflower