Digimarc Corporation

Other

Pinecone Imaging Corporation

Zulutime, LLC

Digimare Corporation

Scientific Imaging Technologies, Inc.

Venture Ad Astra, LLC

Digimarc Coporation

Geoffrey B. Rhoads

Dmrc Corporation

Geoffrey B Rhoads

Tony F Rodriguez

Bruce L Davis

Kenneth Lee Levy

J Scott Carr

Ravi K Sharma

William Y Conwell

Brett Alan Bradley

Ammon E Gustafson

Hugh L Brunk

Brian T MacIntosh

Alastair M Reed

John Douglas Lord

Burt W Perry

Brett T Hannigan

Neil E Lofgren

Tyler J McKinley

Trent J Brundage

Adnan M Alattar

John F Stach

Marc D Miller

Phillip Andrew Seder

Eliot Rogers

Eric D Evans

Joel R Meyer

William C Hein, Iii

Daniel O Ramos

Tomas Filler

Douglas B Evans

Gilbert B Shaw

Philip R Patterson

Rebecca L Gerlach

Nicole Rhoads

Yang Bai

Eoin C Sinclair

R Stephen Hiatt

Edward Bruce Knudson

Scott M Long

Utkarsh Deshmukh

Eric E Ellingson

Kevin C Jones

Robert Craig Brandis

Farid Ahmed

Reed R Stager

Jonathan Scott Carr

Ajith Mulki Kamath

Osama M Alattar

Stephen K Decker

Kurt M Eaton

Clayton L Davidson

Aruna B Kumar

Steven W Stewart

Colin P Cornaby

Conrad Eustis

Mark E Haynes

Jerrine K Owen

Joshua A Rosenthol

Kirstin Hierholzer

Tom Tewalt

Anthony Rodriguez

Harrison Freer

Clay Davidson

Vojtech Holub

Arlie R Conner

Sean Calhoon

Matthew M Weaver

Morley M Blouke

Vahid Sedighianaraki

Joshua V Aller

Mahmood Sher-Jan

Cynthia Louise Archer

Jerry Allen McMahan, Jr

Arthur L Powell

Emma C Sinclair

David A Cushman

Christopher A Ambiel

Marc G Footen

Annalou Vincent

Philip J Stafford

Philip N Reid

William Hein

Neil A Lofgren

Maxfield T Torke

Brian Mosher

Becky G Kiichle-Gross

Adnan V Alattar

Stanley E Graham

Megan I Livermore

Adnam M Alattar

Tony F Rodreguez

Cynthia K Aggson

Lorie Clements

Phillip R Patterson

Tomas Denemark

David L Cavender

Joshua Bickel

Brian T Macintosh

Robert T Durst

Hugh L Brunk Brunk

Two stages of a convolutional neural network are linked by an interconnect that effects a spatial transposition of array data. The spatial transposition can include rotation, scaling, or translation (e.g., in x- or y-directions). A parameter characterizing the transposition (e.g., a parameter identifying rotation angle) can be learned by the same training process that is also used to learn other network parameters, such as layer coefficients. Additionally, or alternatively, data input to a neural network comprises—for each pixel in a patch of imagery—plural data that each indicates a relationship between the value of the pixel, and the value of a neighboring pixel. Some such neural networks can be trained to indicate the presence of a digital watermark signal in the patch of imagery—or a parameter characterizing such a digital watermark signal. Other features and arrangements are also detailed.

Enhanced neural network systems and methods

A steganographic digital watermark signal is decoded from host imagery without requiring a domain transformation for signal synchronization, thereby speeding and simplifying the decoding operation. In time-limited applications, such as in supermarket point-of-sale scanners that attempt watermark decode operations on dozens of video frames every second, the speed improvement allows a greater percentage of each image frame to be analyzed for watermark data. In battery-powered mobile devices, avoidance of repeated domain transformations extends battery life. A great variety of other features and arrangements, including machine learning aspects, are also detailed.

Image-based pose determination

Watermarking is used to track and identify digital images. One claim includes acts of: processing obtained imagery to yield local image information, the local image information being inadequate to reveal a subject depicted in said obtained imagery, using the local image information, resolving geometric distortion of the imagery, the geometric distortion comprising scale and rotation, said resolving yielding geometrically resolved imagery, and detecting the encoded signal from the geometrically resolved imagery using secret detecting information. A great variety of other features and arrangements are also detailed.

Methods and systems for signal processing

Items are identified in a waste stream for purposes of recycling, using deterministic and/or probabilistic techniques. Imagery of the waste stream from multiple viewpoints permit creation of a 3D depth draped image representation, from which one or more 2D planes can be synthesized. Phase-coherent patches of recoverable encoded data can be identified from among soiled and crumpled object surfaces, and used in combination to recover object identification information. Recognition of certain items can trigger further image processing that is specific to such items. (Detection of a catsup bottle, for example, can trigger image analysis to discern the presence of catsup residue.) Information about recognized objects can be provided to external data customers, e.g., to track grey market diversion of particular products into unlicensed territories. These and other features and advantages, which can be used alone or in combination, are detailed herein.

Information-client server built on a rapid material identification platform

A decade from now, a visit to the supermarket will be a very different experience than the familiar experiences of decades past. Product packaging will come alive with interactivity—each object a portal into a rich tapestry of experiences, with contributions authored by the product brand, by the store selling the product, and by other shoppers. The present technology concerns arrangements for authoring and delivering such experiences. A great variety of other features and technologies are also detailed.

Imagery and annotations

A plastic item, such as a beverage bottle, can convey two distinct digital watermarks, encoded using two distinct signaling protocols. A first, printed label watermark conveys a retailing payload, including a Global Trade Item Number (GTIN) used by a point-of-sale scanner in a retail store to identify and price the item when presented for checkout. A second, plastic texture watermark may convey a recycling payload, including data identifying the composition of the plastic. The use of two different signaling protocols assures that a point-of-sale scanner will not spend its limited time and computational resources working to decode the recycling watermark, which may lack data needed for retail checkout. In some embodiments, a recycling apparatus makes advantageous use of both types of watermarks to identify the plastic composition of the item (e.g., relating GTIN to plastic type using an associated database), thereby increasing the fraction of items that are correctly identified for sorting and recycling. In other embodiments the plastic item (or a label thereon) bears only a single watermark. A great number of other features and arrangements are also detailed.

Methods and arrangements for sorting items, useful in recycling

A method for transforming an input array of pixel data into an output array of data, to yield enhanced expression of a digital watermark signal in the output array. One such method includes, for each pixel in the input array, generating a first datum that indicates a value difference between said pixel and a neighboring pixel in a first direction, the first data thereby collectively comprising a first directional difference array. Similarly, for each such pixel in the input array, generating a second datum that indicates a value difference between said pixel and a neighboring pixel in a second direction, the second data thereby collectively comprising a second directional difference array. One or more transforms to a spatial frequency domain are then performed, using these first and second directional difference arrays as input data. First and second results from the one or more transformations are then combined to yield an output array. The just detailed process causes the digital watermark signal in the output array to exhibit a greater signal-to-noise ratio than in the digital watermark signal in the input array. A great number of other features and arrangements are also detailed.

Methods and arrangements for enhanced digital signal detection

In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery captured by conventional or plenoptic cameras can be processed (e.g., by GPUs) to derive several different perspective-transformed views&#x2014;further minimizing the need to manually reposition items for identification. Crinkles and other deformations in product packaging can be optically sensed, allowing such surfaces to be virtually flattened to aid identification. Piles of items can be 3D-modelled and virtually segmented into geometric primitives to aid identification, and to discover locations of obscured items. Other data (e.g., including data from sensors in aisles, shelves and carts, and gaze tracking for clues about visual saliency) can be used in assessing identification hypotheses about an item. Logos may be identified and used&#x2014;or ignored&#x2014;in product identification. A great variety of other features and arrangements are also detailed.

Methods and arrangements for identifying objects

Images depicting items in a waste flow on a conveyor belt are provided to two analysis systems. The first system processes images to decode digital watermark payload data found on certain of the items (e.g., plastic containers). This payload data is used to look up corresponding attribute metadata for the items in a database, such as the type of plastic in each item, and whether the item was used as a food container or not. The second analysis system can be a spectroscopy system that determines the type of plastic in each item by its absorption characteristics. When the two systems conflict in identifying the plastic type, a sorting logic processor applies a rule set to arbitrate the conflict and determine which plastic type is most likely. The item is then sorted into one of several different bins depending on a combination of the final plastic identification, and whether the item was used as a food container or not. A variety of other features and arrangements are also detailed.

Arrangements for digital marking and reading of items, useful in recycling

A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires. In one aspect, the detailed technology concerns phone-based cognition of a scene viewed by the phone's camera. The image processing tasks applied to the scene can be selected from among various alternatives by reference to resource costs, resource constraints, other stimulus information (e.g., audio), task substitutability, etc. The phone can apply more or less resources to an image processing task depending on how successfully the task is proceeding, or based on the user's apparent interest in the task. In some arrangements, data may be referred to the cloud for analysis, or for gleaning. Cognition, and identification of appropriate device response(s), can be aided by collateral information, such as context. A great number of other features and arrangements are also detailed.

Intuitive computing methods and systems

Authenticity of a sticker (e.g., a mark-down sticker on a retail item), or integrity of a closure (e.g., on a delivery bag or package), is confirmed by reference to spatial information. In some embodiments a fingerprint is formed from parameters describing spatial placement of a sticker or pattern on a substrate. In some embodiments a digital watermark pattern provides a spatial frame of reference within which one or more other features can be located. A great many other features and arrangements are also detailed.

Tamper detection arrangements, and point of sales systems employing same

Mobile phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some aspects relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others concern user interface improvements. Other aspects relate to imaging architectures, in which a mobile phone's image sensor is one in a chain of stages that successively act on packetized instructions/data, to capture and later process imagery. Still other aspects relate to distribution of processing tasks between the mobile device and remote resources ('the cloud'). Elemental image processing (e.g., simple filtering and edge detection) can be performed on the mobile phone, while other operations can be referred out to remote service providers. The remote service providers can be selected using techniques such as reverse auctions, through which they compete for processing tasks. A great number of other features and arrangements are also detailed.

Methods and systems for content processing

This patent document discloses physical documents including metameric ink pairs. One claim recites a document comprising: a first surface; a second surface, in which the first surface comprises a first set of print structures and a second set of print structures, in which the first set of print structures and the second set of print structures collective convey an encoded signal discernable from optical scan data representing at least a first portion of the first surface, in which the first set of print structures is provided on the first surface with a first ink and the second set of print structures is provided on the first surface with a second, different ink, and in which the first ink and the second, different ink comprise a metameric pair. Of course, other claims and combinations are described as well.

Authenticating identification and security documents and other objects

The geometric pose of a patch of watermark data is estimated based on the position of a similar, but non-identical, patch of information within a data structure. The information in the data structure corresponds to a tiled array of calibration patterns that is sampled along at least three non-parallel paths. In a particular embodiment, the calibration patterns are sampled so that edges are globally-curved, yet locally-flat. Use of such information in the data structure enables enhanced pose estimation, e.g., speeding up operation, enabling pose estimation from smaller patches of watermark signals, and/or enabling pose estimation from weaker watermark signals. A great variety of other features and arrangements are also detailed.

Watermark sensing methods and arrangements

Growing community of inventors

West Linn, OR, United States of America

Geoffrey B Rhoads