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: 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 raster image processor or press during operation of the press. Various other methods, system configurations and applications 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: In one aspect, a retail store has multiple sensors, including item sensors in a shopping cart for gathering data from a shopper-selected first item. At least certain of the sensor data is provided to a classifier, which was previously-trained (using data including optical data from known items) to identify possible item matches corresponding to data sensed from the first item. An item identification hypothesis that the shopper-selected first item has a particular identity is evaluated based on (a) information from the classifier, and (b) store layout data indicating items associated with a store location visited by the cart or shopper. The item identification hypothesis has a confidence score. If the score meets a criterion, an item of the hypothesized identity is added to a shopping tally. A great number of other features and arrangements are also detailed.

Abstract: In one aspect, a retail store includes a multitude of cameras, including a plurality of 3D cameras, and a plurality of other cameras. Certain of the cameras provide imagery from which a shopper's track through the store is monitored, and certain of the cameras are positioned to detect removal of items from store shelves. The store also includes a computer system that provides a database of information about store layout, indicating stock locations of different items. The computer system receives imagery from the cameras (or information derived from such imagery) and uses this data, together with information from the database and information derived from other sensors in the store, to produce a probabilistic tally of items selected by a store shopper. This tally includes an item bearing a barcode, but is produced without reading the barcode. Each item on the tally is associated with a confidence score that meets a computer system-determined threshold.

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 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: The present disclosure relates to signal processing such as image processing, signal encoding, digital watermarking and data hiding. A sparse or dense digital watermark signal can be conveyed with a narrow-band absorption material corresponding to a center wavelength of a Point of Sale (POS) barcode scanner. The POS barcode scanner typically captures 2D imagery. Since the narrow-band absorption material absorbs over a narrow-band it is relatively imperceptible to the Human Visual System (HVS) but can be seen by the POS scanner.

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: 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: 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.

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: 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: 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: 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: The present disclosure relates to signal processing such as image processing, signal encoding, digital watermarking and data hiding. Technology includes a method comprising: capturing imagery corresponding to a printed object with a red illumination scanner, the red illumination scanner having a wavelength at or around 660 nm, said scanning yielding scan data, wherein the printed object includes a process color printed thereon through an offset or flexo printing press, the process color including a narrow-band absorption material that has a peak absorbance at or around 660 nm, the process color printed in a manner to convey an encoded plural-bit message, the encoded plural-bit message corresponding to a GTIN number; analyzing the imagery with one or more programmed multi-core processors to decode the encoded plural bit message, said analyzing yielding the GTIN number; and providing the GTIN number as an output. Of course other combinations and technology is also provided.

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: 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: 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: 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.