Abstract: 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.

Abstract: Methods employ sensors in portable devices (e.g., smartphones) both to sense content information (e.g., audio and imagery) and context information. Device processing is desirably dependent on both. For example, some embodiments activate certain processor intensive operations (e.g., content recognition) based on classification of sensed content and context. The context can control the location where information produced from such operations is stored, or control an alert signal indicating, e.g., that sensed speech is being transcribed. Some arrangements post sensor data collected by one device to a cloud repository, for access and processing by other devices. Multiple devices can collaborate in collecting and processing data, to exploit advantages each may have (e.g., in location, processing ability, social network resources, etc.). A great many other features and arrangements are also detailed.

Abstract: 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.

Abstract: A sequence of images depicting an object is captured, e.g., by a camera at a point-of-sale terminal in a retail store. The object is identified, such as by a barcode or watermark that is detected from one or more of the images. Once the object's identity is known, such information is used in training a classifier (e.g., a machine learning system) to recognize the object from others of the captured images, including images that may be degraded by blur, inferior lighting, etc. In another arrangement, such degraded images are processed to identify feature points useful in fingerprint-based identification of the object. Feature points extracted from such degraded imagery aid in fingerprint-based recognition of objects under real life circumstances, as contrasted with feature points extracted from pristine imagery (e.g., digital files containing label artwork for such objects).

Abstract: In one aspect, assembly of multi-part food packaging is checked by reference to payloads of steganographically-encoded digital watermarks printed across the packaging components. Marking all surfaces of the packaging components allows arbitrary orientation of feed stock in assembly equipment, and wide latitude in placement of inspection cameras along the packaging line. In another aspect, a scanner at a retail checkout station is alert to any gap detected in steganographic encoding on retail product packaging and, if found, alerts an operator to possible presence of an adhesive label with a misleading barcode. A great variety of others features and arrangements are also detailed.

Abstract: 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—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—or ignored—in product identification. A great variety of other features and arrangements are also detailed.

Abstract: Deterministic identifiers fuel reliable efficient capture of product discovery, purchase and consumption events, which in turn enable more reliable product recommendation, more accurate shopping list generation and in-store navigation. A mobile device, equipped with image and audio detectors, extracts product identifiers from objects, display screens and ambient audio. In conjunction with a cloud-based service, a mobile device application obtains product information and logs product events for extracted identifiers. The cloud service generates recommendations, and mapping for in-store navigation. The detectors also provide reliable and efficient product identification for purchase events, and post shopping product consumption events.

Abstract: 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—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—or ignored—in product identification. A great variety of other features and arrangements are also detailed.

Abstract: This disclosure relates to advanced signal processing technology including signal encoding and digital watermarking. Aspects of the disclosure provide methods, articles of manufacture and systems for determining printing plate inconsistencies, e.g., for printing presses printing encoded images or artwork. Of course, other features and combinations are described as well.

Abstract: 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—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—or ignored—in product identification. A great variety of other features and arrangements are also detailed.

Abstract: The present disclosure relates to signal processing such as digital watermarking and other encoded signals. One claim recites a method of offsetting color casting for a printed object associated with a retail product. The method includes: providing a first additive that absorbs light energy at or around a center wavelength of an illumination source; providing a second additive that absorbs in the ultra-violet spectrum, yet fluoresces at or around the center wavelength of the illumination source, wherein a combination of spectral responses of the first additive and the second additive offset color casting; printing the first additive, second additive and a color on the printed object, wherein the printing conveys an encoded plural bit signal. Of course, other claims and combinations are provided in the specification with reference to specific implementations and related examples.

Abstract: A system senses audio, imagery, and/or other stimulus from a user's environment, and responds to fulfill user desires. In one particular arrangement, a discovery session is launched when the user speaks a cueing expression, which serves to switch the system from a lower activity state to a heightened alert state. The system may recognize that the speech expresses a user request that requires analysis of camera-captured imagery to fulfill. In response the system can apply an operation, such as a recognition operation (e.g., barcode decoding), to the imagery and take an action based on resulting information. Operation of the system can be aided by collateral information, such as context. A great number of other features and arrangements are also detailed.

Abstract: This disclosure details image and audio signal processing methods and associated equipment to robustly encode transaction parameters in rendered displays, printed objects and audio. It also details corresponding decoding methods and equipment to recover these parameters. Further, it details object authentication processing and equipment to validate a transaction for an object, employing a trust network protocol for maintaining a trusted transaction history of the object. Various alternative forms of this technology are described.

Abstract: 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—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. A great variety of other features and arrangements are also detailed.

Abstract: Digital watermarking is adapted for the variable data printing. A reference signal serves as a proxy for optimizing the embedding a watermark in a host image to be printed. Using the reference signal, embedding parameters are generated, which are a function of constraints such as visual quality and robustness of the machine readable data. Adjustments needed to embed a unique payload in each printed piece are generated using the embedding parameters. These adjustments are stored in a manner that enables them to be efficiently obtained and applied within the RIP or press during operation of the press. Various other methods, system configurations and applications are also detailed.

Abstract: An automatic object identification scanner is equipped with recognition units that provide detection results for objects and a controller that resolves potential conflicts in the results. One form of recognition unit detects product identifiers and flags in a digital payload that is encoded redundantly across packaging or labels applied to packaging. The controller gets detection results and evaluates them relative to a state data structure, which maintains state for identifiers obtained within a time interval, such as a timeout interval or waiting period after a detection result. Identifiers are reported to a POS system depending on logic that evaluates code priority and pending waiting periods.

Abstract: Imagery captured by an autonomous robot is analyzed to discern digital watermark patterns. In some embodiments, identical but geometrically-inconsistent digital watermark patterns are discerned in an image frame, to aid in distinguishing multiple depicted instances of a particular item. In other embodiments, actions of the robot are controlled or altered in accordance with image processing performed by the robot on a digital watermark pattern. The technology is particularly described in the context of retail stores in which the watermark patterns are encoded, e.g., on product packaging, shelving, and shelf labels. A great variety of other features and arrangements are also detailed.

Abstract: Methods employ sensors in portable devices (e.g., smartphones) both to sense content information (e.g., audio and imagery) and context information. Device processing is desirably dependent on both. For example, some embodiments activate certain processor intensive operations (e.g., content recognition) based on classification of sensed content and context. The context can control the location where information produced from such operations is stored, or control an alert signal indicating, e.g., that sensed speech is being transcribed. Some arrangements post sensor data collected by one device to a cloud repository, for access and processing by other devices. Multiple devices can collaborate in collecting and processing data, to exploit advantages each may have (e.g., in location, processing ability, social network resources, etc.). A great many other features and arrangements are also detailed.

Abstract: 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.

Abstract: Digital encoding methods are used to encode digital payloads in image and conductive ink carriers. These carriers are applied to objects by various printing technologies, together in one or more ink formulations or in separate ink layers on an object. The image payload is extracted from an image sensed with image sensor, while the conductive ink payload is extracted from an image sensed with a capacitive or resistive sensor or like device for sensing the modulation in conductivity of the printed conductive ink elements.