Digimarc Corporation

Eoin C Sinclair

Geoffrey B Rhoads

Bruce L Davis

Brian T MacIntosh

Edward Bruce Knudson

Eliot Rogers

Colin P Cornaby

An illustrative implementation of the technology includes three primary components: a desktop application, a mobile phone application, and connections to retailer inventory and pricing APIs (e.g., for Walmart and/or Best Buy). The experience begins with the consumer going to an online retailer's website (e.g., Amazon) to search for a product. The desktop application automatically searches for the same product using the APIs of Walmart and/or Best Buy. If matches and near-matches of the product are found, the product name, model, price, and local availability at affiliate locations are shown. With a mobile phone camera-scan of the product page, relevant information is transferred to the consumer's phone. From there, the consumer can interact with the options on the mobile phone to be directed to the nearby brick and mortar store of choice carrying that product at the price they want. Along the way, the retailer can present offers and additional product information directly to the consumer. A great variety of other technologies and arrangements are also detailed.

Methods and arrangements including data migration among computing platforms, e.g. through use of audio encoding

A camera captures video imagery depicting a digitally-watermarked object. A reference signal in the watermark is used to discern the pose of the object relative to the camera, and this pose is used in affine-transforming and positioning a graphic on the imagery as an augmented reality overlay. Feature points are also discerned from the captured imagery, or recalled from a database indexed by the watermark. As the camera moves relative to the object, the augmented reality overlay tracks the changing object depiction, using these feature points. When feature point-based tracking fails, the watermark is again processed to determine pose, and the overlay presentation is updated accordingly. In another arrangement, feature points are extracted from images of supermarket objects captured by multiple users, and are compiled in a database in association with watermark data identifying the objects&#x2014;serving as a crowd-sourced repository of feature point data. A great number of other features and arrangements are also detailed.

Hybrid feature point/watermark-based augmented reality

In an exemplary embodiment, image content is rendered to include a digital watermark pattern at an essentially fixed scale, regardless of the size of screen on which the content is displayed. In one particular embodiment, CSS and JavaScript are responsive to the rendering context (which can include screen size, and/or viewer position) to define the geometry of a watermarked texture block, which is tiled to serve as a background of an HTML-defined page. A great variety of other features and arrangements are also detailed.

Screen watermarking methods and arrangements

Mobile devices, such as smartphones, are severely battery-limited. The capabilities of mobile device processors have increased at exponential rates, but battery technologies have improved at much slower rates. As a consequence, it is ever more important that mobile devices be operated in battery-preserving manners. An aspect of the present technology concerns methods and arrangements enabling on-going recognition-processing of imagery and audio by different detectors, without the high battery drain that has characterized the prior art. A variety of other features and arrangements are also detailed.

Method and apparatus for analyzing sensor data

An illustrative implementation of the technology includes three primary components: a desktop application, a mobile phone application, and connections to retailer inventory and pricing APIs (e.g., for Walmart and/or Best Buy). The experience begins with the consumer going to an online retailer's website (e.g., Amazon) to search for a product. The desktop application automatically searches for the same product using the APIs of Walmart and/or Best Buy. If matches and near-matches of the product are found, the product name, model, price, and local availability at affiliate locations is shown. With a mobile phone camera-scan of the product page, relevant information is transferred to the consumer's phone. From there, the consumer can interact with the options on the mobile phone to be directed to the nearby brick and mortar store of choice carrying that product at the price they want. Along the way, the retailer can present offers and additional product information directly to the consumer. A great variety of other technologies and arrangements are also detailed.

Methods and arrangements including data migration among computing platforms, e.g. through use of steganographic screen encoding

An illustrative implementation of the technology includes three primary components: a desktop application, a mobile phone application, and connections to retailer inventory and pricing APIs (e.g., for Walmart and/or Best Buy). The experience begins with the consumer going to an online retailer's website (e.g., Amazon) to search for a product. The desktop application automatically searches for product matches using the APIs of affiliated retailers. If matches and near-matches of the product are found, the product name, model, price, and local availability at affiliate locations is shown. With a mobile phone camera-scan of the product page, relevant information is transferred to the consumer's phone. From there, the consumer can interact with the options on the mobile phone to be directed to the nearby brick and mortar store of choice carrying that product at the price they want. Along the way, the retailer can present offers and additional product information directly to the consumer. A great variety of other technologies and arrangements are also detailed.

Methods and arrangements including data migration among computing platforms, E.G. through use of steganographic screen encoding

Arrangements involving portable devices (e.g., smartphones and tablet computers) are disclosed. One arrangement enables a content creator to select software with which that creator's content should be rendered&#x2014;assuring continuity between artistic intention and delivery. Another utilizes a device camera to identify nearby subjects, and take actions based thereon. Others rely on near field chip (RFID) identification of objects, or on identification of audio streams (e.g., music, voice). Some technologies concern improvements to the user interfaces associated with such devices. For example, some arrangements enable discovery of both audio and visual content, without any user requirement to switch modes. Other technologies involve use of these devices in connection with shopping, text entry, and vision-based discovery. Still other improvements are architectural in nature, e.g., relating to evidence-based state machines, and blackboard systems. Yet other technologies concern computational photography. A great variety of other features and arrangements are also detailed.

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Portland, OR, United States of America

Eoin C Sinclair