Abstract: An object (e.g., a driver's license) is tested for authenticity using imagery captured by a consumer device (e.g., a mobile phone camera). Corresponding data is sent from the consumer device to a remote system, which has secret knowledge about features indicating object authenticity. The phone, or the remote system, discerns the pose of the object relative to the camera from the captured imagery. The remote system tests the received data for the authentication features, and issues an output signal indicating whether the object is authentic. This testing involves modeling the image data that would be captured by the consumer device from an authentic object—based on the object's discerned pose (and optionally based on information about the camera optics), and then comparing this modeled data with the data sent from the consumer device. A great variety of other features and arrangements are also detailed.

Abstract: A portable computing device captures imagery from a screen of a second computer, decodes information steganographically-encoded in the screen display, and uses the decoded information to establish a secure session with the second computer. Such technology enables a help-desk staffer to interact with a client's desktop computer, without touching the keyboard of the desktop computer, and without interrupting the client's work. A great many other features and arrangements are also detailed.

Abstract: A device 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 device-based cognition of a scene viewed by the device's camera. Tasks, which can be selected with the aid of context, are allocated increased or decreased resources based on data comprising (a) user input data indicating express or implied encouragement or discouragement of the task and/or (b) a detection state metric, representing a quantified likelihood that a goal sought by the task will be reached. A great number of 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 space-time calibration system and method implement space-time solutions, in which, in one preferred embodiment, a single node determines its own space-time solutions based on other network nodes with which the single node communicates. In other preferred embodiments, space-time solutions for the node can be generated using other resources in the network. The disclosed system and method enable reliable, precise object positioning particularly for environments where the Global Positioning System (GPS) is blocked or subject to interference such as within the urban core.

Abstract: A spectral imaging device is configured to capture color images synchronized with controlled illumination from different color light emitting diodes. A processor in the device applies a coupling factor to sampled color images to convert sampled pixels into spectral channels corresponding to LED color and color filter. Multi-spectral spectricity vectors produced at pixel locations are used along with spatial information to classify objects, such as produce items.

Abstract: A method for obtaining object surface topology in which image frames of a scene (e.g., video frames from a user passing a smartphone camera over an object) are transformed into dense feature vectors, and feature vectors are correlated to obtain high precision depth maps. Six dimensional pose is determined from the video sequence, and then used to register patches of pixels from the frames. Registered patches are aligned and then correlated to local shifts. These local shifts are converted to precision depth maps, which are used to characterize surface detail of an object. Feature vector transforms are leveraged in a signal processing method comprising several levels of interacting loops. At a first loop level, a structure from motion loop process extracts anchor features from image frames. At another level, an interacting loop process extracts surface texture, as noted. At additional levels, object forms are segmented from the images, and objects are counted and/or measured.

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: 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 and arrangements involving portable user devices such smartphones and wearable electronic devices are disclosed, as well as other devices and sensors distributed within an ambient environment. Some arrangements enable a user to perform an object recognition process in a computationally- and time-efficient manner. Other arrangements enable users and other entities to, either individually or cooperatively, register or enroll physical objects into one or more object registries on which an object recognition process can be performed. Still other arrangements enable users and other entities to, either individually or cooperatively, associate registered or enrolled objects with one or more items of metadata. A great variety 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 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.

Abstract: Information is encoded in an image signal by exploiting spectral differences between colors that appear the same when rendered. These spectral differences are detected using image sensing that discerns the spectral differences. Spectral difference detection methods include using sensor-synchronized spectrally-structured-light imaging, 3D sensors, imaging spectrophotometers, and higher resolution Bayer pattern capture relative to resolution of patches used to convey a spectral difference signal.

Abstract: The application discloses apparatus and systems for authenticating physical object, identification documents and security documents. Some such methods and apparatus involve signal encoding or digital watermarking.

Abstract: An object (e.g., a driver's license) is tested for authenticity using imagery captured by a consumer device (e.g., a mobile phone camera). Corresponding data is sent from the consumer device to a remote system, which has secret knowledge about features indicating object authenticity. The phone, or the remote system, discerns the pose of the object relative to the camera from the captured imagery. The remote system tests the received data for the authentication features, and issues an output signal indicating whether the object is authentic. This testing involves modeling the image data that would be captured by the consumer device from an authentic object—based on the object's discerned pose (and optionally based on information about the camera optics), and then comparing this modeled data with the data sent from the consumer device. A great variety of 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: In one particular aspect, a portable computing device (e.g., a tablet or smartphone) senses audio and/or image content from a user's environment, and initiates one or more recognition agents (e.g., performing image watermark recognition, image recognition, object recognition, facial recognition, barcode recognition, optical character recognition, audio watermark recognition, speech recognition, speaker recognition, or music recognition). Resource allocation to a recognition agent can be varied based on (a) progress of the recognition agent to achieve its recognition goal, and (b) user interest data indicating user interest in the output of the recognition agent. A second candidate recognition agent can be evaluated for possible launch, based on a relevance score, and a cost score. In some embodiments, the device adapts its operation to changing context, by terminating a first recognition agent in favor of a second recognition agent, without express user instruction to do so.

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 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. Recognition tasks, selected with the aid of context, are allocated increased or decreased resources based on data comprising (a) user input data indicating express or implied encouragement or discouragement of the recognition task and/or (b) a detection state metric, representing a quantified likelihood that the recognition goal sought by the recognition task will be reached. A great number of other features and arrangements are also detailed.

Abstract: Phasor Measurement Units (PMUs) tend to be specialized and expensive—relegated to only key points in power distribution networks, and are generally reliant on GPS technology. The present disclosure details how any smart meter—using wireless communication—can perform sub-microsecond-grade synchrophasor measurements. Other aspects concern smart meter-based determination of A, B or C phase of the tri-phase power network. This can involve count-stamp enabling message packets sent to and/or from a smart meter, and then associating such count-stamps to local measurements of power phase by a metrology unit. Once a network of such enabled smart meters and other devices is formed, sub-microsecond metropolitan-wide and entire region-wide synchronizing time standard can calibrate local measurements of power phase, where simple A, B and C phase determination is one low hanging fruit application of such.

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.