Abstract: A customer who visits an online marketplace to view information regarding an item formed from fabric may request and receive instructions for producing a sample of the fabric that mimics the sensations of touch and feel of the fabric. The sample may be produced using an automated fabricator, such as a 3D printer, associated with a client device from which the customer made the request. The instructions may include or describe a digital model of the fabric, customized for the automated fabricator. In particular, the sample may be formed from various plastics or other materials that are accessible to the automated fabricator, and need not be formed from the actual materials that are included in the fabric.

Abstract: Provided herein is are computer-implemented methods, computer-implemented systems, and non-transitory computer-readable storage media for registering a user's eye gaze profile via a mobile device having a screen and a front facing camera. Also provided herein is are computer-implemented methods, computer-implemented systems, and non-transitory computer-readable storage media for determining a spoofing attempt by a user during a request to access a resource via a mobile device.

Abstract: Provided herein are devices, systems, and methods for detecting spoofing of a 3D object, using a 2D representation, in a mobile object authentication process, comprising capturing image data of the 3D object by a front-facing camera, to record a current spatial characteristic of the 3D object, while a front-facing screen displays an authentication pattern comprising a plurality of regions, wherein at least one of the regions varies in at least one of: brightness, position, size, shape, and color over time causing a variance of lighting effects which create highlights and shadows on the 3D object over time. The devices, systems, and methods thereby provide an efficient and secure process for determining if spoofing of the 3D object, using a 2D representation, is attempted in a mobile authentication process, by comparing the current spatial characteristic of the 3D object with a stored reference spatial characteristic of the 3D object.

Abstract: Described are methods, systems, and medias for detecting spoofing of biometric identity recognition and/or validating an identity recognition match by using the camera of a mobile device, processing the user's face image or set of images at a first and second distance to generate first and second data representations, processing the first data representation into a predictive model, and comparing the data representation with the predictive model.

Abstract: Items, such as produce items, may be placed in containers, imaged, weighed, and stored for subsequent retrieval. Images that depict the items and attributes associated with the items may be presented to customers via an interface. Upon receiving an indication that a customer has purchased one or more items via the interface, a container that includes the one or more items is retrieved. The one or more items are removed from the container and packaged for delivery to the customer. The resulting empty container is refilled with new items, which are then imaged, weighed, and stored.

Abstract: Provided herein is are computer-implemented methods, computer-implemented systems, and non-transitory computer-readable storage media for registering a user's eye gaze profile via a mobile device having a screen and a front facing camera. Also provided herein is are computer-implemented methods, computer-implemented systems, and non-transitory computer-readable storage media for determining a spoofing attempt by a user during a request to access a resource via a mobile device.

Abstract: Disclosed are various examples that relate to providing an alternative viewing experience for video content. A semantic graph corresponding to the content is generated. The semantic graph is traversed and the video content segments corresponding to a selected attribute within the semantic graph are played back in an ordering that can vary from a linear representation of the content.

Abstract: Provided herein are devices, systems, and methods for detecting spoofing of a 3D object, using a 2D representation, in a mobile object authentication process, comprising capturing image data of the 3D object by a front-facing camera, to record a current spatial characteristic of the 3D object, while a front-facing screen displays an authentication pattern comprising a plurality of regions, wherein at least one of the regions varies in at least one of: brightness, position, size, shape, and color over time causing a variance of lighting effects which create highlights and shadows on the 3D object over time. The devices, systems, and methods thereby provide an efficient and secure process for determining if spoofing of the 3D object, using a 2D representation, is attempted in a mobile authentication process, by comparing the current spatial characteristic of the 3D object with a stored reference spatial characteristic of the 3D object.

Abstract: Described are methods, systems, and medias for detecting spoofing of biometric identity recognition and/or validating an identity recognition match by using the camera of a mobile device, processing the user's face image or set of images at a first and second distance to generate first and second data representations, processing the first data representation into a predictive model, and comparing the data representation with the predictive model.

Abstract: Identifiers or references to supplemental information or content regarding images may be steganographically encoded into the images. The identifiers or references may be encoded into least significant bits or less significant bits of pixels within the image that may be selected on any basis. The identifiers or references may include alphanumeric characters, bar codes, symbols or other features. When an image is captured of an image having one or more identifiers or references steganographically encoded therein, the identifiers or references may be interpreted, and the supplemental information or content may be accessed and displayed on a computer display. In some embodiments, the supplemental information or content may identify and relate to a commercial product expressed in an image, and may include a link to one or more pages or functions for purchasing the commercial product.

Abstract: Provided herein are devices, systems, and methods for detecting spoofing of a 3D object, using a 2D representation, in a mobile object authentication process, comprising capturing image data of the 3D object by a front-facing camera, to record a current spatial characteristic of the 3D object, while a front-facing screen displays an authentication pattern comprising a plurality of regions, wherein at least one of the regions varies in at least one of: brightness, position, size, shape, and color over time causing a variance of lighting effects which create highlights and shadows on the 3D object over time. The devices, systems, and methods thereby provide an efficient and secure process for determining if spoofing of the 3D object, using a 2D representation, is attempted in a mobile authentication process, by comparing the current spatial characteristic of the 3D object with a stored reference spatial characteristic of the 3D object.

Abstract: Items, such as produce items, may be placed in containers, imaged, weighed, and stored for subsequent retrieval. Images that depict the items and attributes associated with the items may be presented to customers via an interface. Upon receiving an indication that a customer has purchased one or more items via the interface, a container that includes the one or more items is retrieved. The one or more items are removed from the container and packaged for delivery to the customer. The resulting empty container is refilled with new items, which are then imaged, weighed, and stored.

Abstract: A customer who visits an online marketplace to view information regarding an item formed from fabric may request and receive instructions for producing a sample of the fabric that mimics the sensations of touch and feel of the fabric. The sample may be produced using an automated fabricator, such as a 3D printer, associated with a client device from which the customer made the request. The instructions may include or describe a digital model of the fabric, customized for the automated fabricator. In particular, the sample may be formed from various plastics or other materials that are accessible to the automated fabricator, and need not be formed from the actual materials that are included in the fabric.

Abstract: A reflected light identification (RLID) system uses light to communicate stored information across long distances with minimal interference. The RLID system may include a light source that directs an incident light signal to an RLID structure, which then transmits an encoded light signal to a sensor. The RLID system may include a passive RLID structure (i.e., a structure that does not include power source) such as an RLID reflection surface that includes layered reflective films that reflect the incident light signal back in multiple reflections that serially encodes data. The RLID system may also include an active RLID structure (i.e., a structure that includes power source) that uses energy harvesting to extract and accumulate power from an incident light signal, and then uses the harvested energy to transmit a return signal.

Abstract: Directed fragmentation of an unmanned aerial vehicle (UAV) is described. In one embodiment, the UAV includes various components, such one or more motors, batteries, sensors, a housing, casing or shell, and a payload for delivery. Additionally, the UAV includes a controller. The controller determines a flight path and controls a flight operation of the UAV. During the flight operation, the controller develops a release timing and a release location for one or more of the components based on the flight path, the flight conditions, and terrain topology information, among other factors. The controller can also detect a disruption in the flight operation of the UAV and, in response, direct fragmentation of one or more of the components apart from the UAV. In that way, a controlled, directed fragmentation of the UAV can be accomplished upon any disruption to the flight operation of the UAV.

Abstract: Systems may include a storage location and a bladder. The storage location may have a volume. The bladder may be selectively inflatable and deflatable to change an amount of the volume of the storage location that is occupied by the bladder. Fluid communication between the bladder and an inflation network may change an amount of pressurized fluid present in the bladder so as to change the amount of the volume of the storage location occupied by the bladder. For example, this may cause the bladder to press against an item in the storage location, such as to secure the item or to facilitate a determination of an amount of space that is occupied in the storage location and/or an amount of space that is available for receipt of additional items.

Abstract: Three-dimensional models of objects may be generated according to adaptive depth sensing techniques. An imaging device may include a projector that is configured to project light (e.g., infrared light) onto selected portions of a scene, and a depth imaging sensor configured to capture reflections of the projected light. The projector may be used to project points of light onto aspects of a scene having high degrees of variation of depth, color, texture, curvature or other attributes, where an increased number of depth values may be required to accurately depict a profile of an object within a scene, and to avoid projecting light onto aspects of the scene having low degrees of variation of depth, color, texture, curvature or such other attributes, where the profile of the object may be accurately represented by comparatively fewer depth values.

Abstract: Items, such as produce items, may be placed in containers, imaged, weighed, and stored for subsequent retrieval. Images that depict the items and attributes associated with the items may be presented to customers via an interface. Upon receiving an indication that a customer has purchased one or more items via the interface, a container that includes the one or more items is retrieved. The one or more items are removed from the container and packaged for delivery to the customer. The resulting empty container is refilled with new items, which are then imaged, weighed, and stored.

Abstract: 3D models of objects in motion may be generated using depth imaging data and visual imaging data captured at different times. A 3D model of an object in motion at a first position may be generated at a first time and projected forward to a second position corresponding to a second time. Imaging data captured from the object at the second position at the second time may be compared to the projected-forward 3D model of the object at the second position. Differences between the imaging data and the projected-forward 3D model may be used to modify the 3D model, as necessary, until an accurate and precise 3D representation of the object has been derived.

Abstract: Techniques for automated quality control of containers and items are disclosed. Images of a container can be successively captured over time. A consolidated image can be generated from the captured images. A non-image representation of the consolidated image can be determined. The non-image representation can be used to determine whether the container satisfies a condition. An imaging system can include a visual reference object or an object sensor used to detect entry of the container into a view volume of an electronic camera. A motion system can transport the container into the view volume. Some examples operate in an automated-warehouse environment.