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: Systems, devices, and methods for precision boom deployment are provided in accordance with various embodiments. The tools and techniques provided may have space and/or terrestrial applications. Some embodiments include a boom deployment system that may include a furlable boom. Some embodiments include: boom reinforcement devices, end fitting devices, contoured support devices, edge support devices, spiral harness devices, latch devices, combined boom spool and tension drive devices, and/or rotary encoder devices. Some embodiments may utilize a composite slit-tube boom. Some embodiments utilize a furlable boom that may be fabricated with curvature along its length.

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 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: 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: 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—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. Others involve use of these devices in connection with shopping, text entry, sign language interpretation, 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 use of linked data in portable devices—some of which exploit GPU capabilities. Still other technologies concern computational photography.

Abstract: Systems, devices, and methods for precision boom deployment are provided in accordance with various embodiments. The tools and techniques provided may have space and/or terrestrial applications. Some embodiments include a boom deployment system that may include a furlable boom. Some embodiments include: boom reinforcement devices, end fitting devices, contoured support devices, edge support devices, spiral harness devices, latch devices, combined boom spool and tension drive devices, and/or rotary encoder devices. Some embodiments may utilize a composite slit-tube boom. Some embodiments utilize a furlable boom that may be fabricated with curvature along its length.

Abstract: Content uploaded to a video distribution service is analyzed to determine if a portion matches part of any reference work. If a match is found, treatment of the uploaded content is determined based on stored rule data, and based on one or more factors. These factors can include, e.g., the length of the matching portion, the part of the reference work from which the matching portion was apparently copied, the confidence of the match, the popularity of the uploaded content (or of the reference work), the geography from which the content was uploaded (or the geography to which it is to be downloaded), etc. Further determinations may be made by human evaluators (including crowd-source approaches). A great variety of other features and arrangements are also detailed.

Abstract: A variety of technologies having practical application in retail stores are detailed. One is an improved method of identifying items selected by customers. This method includes receiving sensor data from plural sensors, including (a) ceiling-mounted cameras that monitor tracks of customers through aisles of the store, and (b) inventory sensors that are positioned to monitor removal of stock from store shelves. This received sensor data is employed in evaluating plural alternate item identification hypotheses. These hypotheses include a first hypothesis that a customer selected an item having a first identity, and a second hypothesis that the customer selected an item having a second identity. A confidence score is associated with each of the first and second item selection hypotheses. These confidence scores are refined as sensor data is received, e.g., increasing a confidence score of one hypothesis, and reducing a confidence score of another.

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.

Abstract: 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.

Abstract: Reference imagery of dermatological conditions is compiled in a crowd-sourced database (contributed by clinicians and/or the lay public), together with associated diagnosis information. A user later submits a query image to the system (e.g., captured with a smartphone). Image-based derivatives for the query image are determined (e.g., color histograms, FFT-based metrics, etc.), and are compared against similar derivatives computed from the reference imagery. This comparison identifies diseases that are not consistent with the query image, and such information is reported to the user. Depending on the size of the database, and the specificity of the data, 90% or more of candidate conditions may be effectively ruled-out, possibly sparing the user from expensive and painful biopsy procedures, and granting some peace of mind (e.g., knowledge that an emerging pattern of small lesions on a forearm is probably not caused by shingles, bedbugs, malaria or AIDS).

Abstract: Self-checkout technologies for retail stores are improved by incorporation of enhanced fraud detection arrangements. For example, if a shopper enters an item on a self-checkout tally, while positioned at a location remote from the normal stock location for that item, a responsive action may be taken. Likewise, if a shopper enters the same item on a self-checkout tally twice, at widely separated times, a responsive action may be taken. These responsive actions can include dispatching a store clerk to assist the shopper, or increasing a risk score that is repeatedly re-calculated during the shopper's visit. A great variety of other features and arrangements (e.g., powering arrangements for mobile phones in shopping carts) are also detailed.

Abstract: 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—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. Others involve use of these devices in connection with shopping, text entry, sign language interpretation, 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 use of linked data in portable devices—some of which exploit GPU capabilities. Still other technologies concern computational photography.

Abstract: Art can be infused with network identifiers at the time of its creation, rather than as a post-process. The identifiers may be encoded as overt elements of the art, and enable the artist to reprogram—as over time—an augmentation of the artwork experience via network-delivered components. These network components can include stimuli present when the artist created the work (e.g., music), commentary by the artist, video and augmented reality features, audience-crowdsourced content (e.g., imagery of, or feedback provided by, other viewers encountering the artwork), etc. The artwork augmentation can vary with the user's context (e.g., location, demographics, interests, history). Physical brushes can be equipped to insert such identifiers in graphic arts; other authoring tools are disclosed as well. The network experience can be delivered via smartphones, projectors, and other devices. A great number of other features and arrangements are also detailed.

Abstract: A variety of technologies having practical application in retail stores are detailed. One is an improved method of identifying items selected by customers. This method includes receiving sensor data from plural sensors, including (a) ceiling-mounted cameras that monitor tracks of customers through aisles of the store, and (b) inventory sensors that are positioned to monitor removal of stock from store shelves. This received sensor data is employed in evaluating plural alternate item identification hypotheses. These hypotheses include a first hypothesis that a customer selected an item having a first identity, and a second hypothesis that the customer selected an item having a second identity. A confidence score is associated with each of the first and second item selection hypotheses. These confidence scores are refined as sensor data is received, e.g., increasing a confidence score of one hypothesis, and reducing a confidence score of another.

Abstract: 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.

Abstract: Content uploaded to a video distribution service is analyzed to determine if a portion matches part of any reference work. If a match is found, treatment of the uploaded content is determined based on stored rule data, and based on one or more factors. These factors can include, e.g., the length of the matching portion, the part of the reference work from which the matching portion was apparently copied, the confidence of the match, the popularity of the uploaded content (or of the reference work), the geography from which the content was uploaded (or the geography to which it is to be downloaded), etc. Further determinations may be made by human evaluators (including crowd-source approaches). A great variety of other features and arrangements are also detailed.

Abstract: Reference imagery of dermatological conditions is compiled in a crowd-sourced database (contributed by clinicians and/or the lay public), together with associated diagnosis information. A user later submits a query image to the system (e.g., captured with a smartphone). Image-based derivatives for the query image are determined (e.g., color histograms, FFT-based metrics, etc.), and are compared against similar derivatives computed from the reference imagery. This comparison identifies diseases that are not consistent with the query image, and such information is reported to the user. Depending on the size of the database, and the specificity of the data, 90% or more of candidate conditions may be effectively ruled-out, possibly sparing the user from expensive and painful biopsy procedures, and granting some peace of mind (e.g., knowledge that an emerging pattern of small lesions on a forearm is probably not caused by shingles, bedbugs, malaria or AIDS).