At a high level, embodiments of the invention relate to augmenting video data with presence data derived from one or more proximity tags. More specifically, embodiments of the invention generate forensically authenticated recordings linking video imagery to the presence of specific objects in or near the recording. One embodiment of the invention includes video recording system comprising a camera, a wireless proximity tag reader, a storage memory and control circuitry operable to receive image data from the camera receive a proximity tag identifier identifying a proximity tag from the proximity tag reader, and store an encoded frame containing the image data and the proximity tag identity in the storage memory.

Embodiments relate to using sensor data and location data from a device to generate augmented reality images. A mobile device pose can be determined (a geographic position, direction and a three dimensional orientation of the device) within a location. A type of destination in the location can be identified and multiple destinations can be identified, with the mobile device receiving queue information about the identified destinations from a server. A first image can be captured. Based on the queue information, one of the identified destinations can be selected. The geographic position of each identified destination can be identified, and these positions can be combined with the mobile device pose to generate a second image. Finally, an augmented reality image can be generated by combining the first image and the second image, the augmented reality image identifying the selected one destination.

A bulk feeder includes a feeder main body, a track member having a reception region in which multiple components discharged from a component case accommodating the components in a bulk state are received, a supply region to which the components are supplied, and a conveyance path of the components from the reception region to the supply region, a vibration device configured to apply vibration to the track member such that the components on the conveyance path are conveyed, and an alignment member configured to guide the multiple components conveyed by the vibration of the track member and align the components with respect to the feeder main body.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize a neural network having a long short-term memory encoder-decoder architecture to progressively modify a digital image in accordance with a natural language request. For example, in one or more embodiments, the disclosed systems utilize a language-to-operation decoding cell of a language-to-operation neural network to sequentially determine one or more image-modification operations to perform to modify a digital image in accordance with a natural language request. In some cases, the decoding cell determines an image-modification operation to perform partly based on the previously used image-modification operations. The disclosed systems further utilize the decoding cell to determine one or more operation parameters for each selected image-modification operation. The disclosed systems utilize the image-modification operation(s) and operation parameter(s) to modify the digital image (e.g., by generating one or more modified digital images) via the decoding cell.

Systems, computer program products, and methods are described herein for implementing steganography based augmented reality platform. The present invention is configured to provide an augmented reality application for installation on a computing device of a user; receive, via the augmented reality application, a real-time visual feed, wherein the real-time visual feed comprises an image, wherein the image comprises a message that is steganographically embedded therein; determine that the computing device of the user is authorized to access the message embedded in the image in the visual feed; and generate an acknowledgement that the computing device of the user is authorized to access the message embedded in the image in the visual feed; and transmit control signals configured to cause the computing device of the user to overlay, via the augmented reality application, the acknowledgement in a vicinity of the image in the real-time visual feed.

The disclosed computer-implemented method includes determining that audio quality is to be adjusted for a multimedia streaming connection over which audio data and video data are being streamed to a content player. The audio data is streamed at a specified audio quality level and the video data is streamed at a specified video quality level. The method also includes determining that a specified minimum video quality level is to be maintained while adjusting the audio quality level. Still further, the method includes dynamically adjusting the audio quality level of the multimedia streaming connection while maintaining the video quality level of the multimedia streaming connection at at least the specified minimum video quality level. Various other methods, systems, and computer-readable media are also disclosed.

Techniques including obtaining a first location of a vehicle, the vehicle having two or more cameras disposed about the vehicle, each camera associated with a physical camera pose, capturing, by a first camera, a first image of a first area in a first field of view, associating the first image with the first location of the vehicle when the first image was captured, moving the vehicle in a direction so that the first area is in an expected second field of view of a second camera, wherein the second camera is not capturing images, obtaining a second location of the vehicle, determining a temporal camera pose based on a first physical camera pose, a second physical camera pose, and the second location of the vehicle, and rendering a view of the first area from the expected second field of view of the second camera based on the first image.

Exemplary systems and methods are disclosed for detecting embedded data in a digital image. The system includes a processing device that extracts one or more features from a digital image and analyzes the one or more extracted features in a plurality of steganography analyzers, each steganography analyzer configured to execute a different steganography algorithm. The processing device generates an output data value at each steganography analyzer, the output data value indicating a probability that the digital image includes steganography according to the steganography algorithm of the steganography analyzer. Each output probability value is fed to an ensemble classifier, the ensemble classifier including a neural network in which the output probability values of the plurality of steganography analyzers are ensembled together to generate an output ensemble data value indicating a probability that the digital image includes any steganography according to the steganography algorithms of the steganography analyzers.

Scene perception systems and methods are described herein. In certain illustrative examples, a system combines data sets associated with imaging devices included in a dynamic multi-device architecture and uses the combined data sets to perceive a scene (e.g., a surgical scene) imaged by the imaging devices. To illustrate, the system may access tracking data for imaging devices capturing images of a scene and fuse, based on the tracking data, data sets respectively associated with the imaging devices to generate fused sets of data for the scene. The tracking data may represent a change in a pose of at least one of the image devices that occurs while the imaging devices capture images of the scene. The fused sets of data may represent or be used to generate perceptions of the scene. In certain illustrative examples, scene perception is dynamically optimized using a feedback control loop.

Provided is an imaging device including: an imaging unit (130) that generates a one frame image by sequentially receiving each reflected light reflected by a subject by intermittently and sequentially irradiating the subject with each irradiation light having a different wavelength according to a position of the moving subject, temporarily and sequentially holding signal information based on the reflected light of each wavelength, and collectively reading the held signal information; and a combining unit (140) that generates a combined image by cutting a subject image corresponding to the reflected light of each wavelength from the one frame image and superimposing a plurality of the cut subject images.