Abstract: Devices, methods, and non-transitory program storage devices (NPSDs) are disclosed herein to provide for the privacy-respectful learning of iconic scenes and places, wherein the learning is based on information received from one or more client devices in response to one or more collection criteria specified as part of one or more collection operations launched by a server device. In some embodiments, differential privacy techniques (such as the submission of predetermined amounts of noise-injecting, e.g., randomly-generated, data in conjunction with actual data) are employed by the client devices, such that any insights learned by the server device only relate to “hot spots,” “themes,” or other scenes, objects, and/or topics that are highly popular and captured in the digital assets (DAs) of many users, ensuring there is no way for the server device to learn or glean any insights related to particular users of individual client devices participating in the collection operations.

Abstract: This disclosure relates to systems, methods, and computer-readable media for identifying digital assets on the end-user device and received from another device as the secondary digital assets; adding the secondary digital assets to a syndication library separate from the primary photo library; and applying eligibility filters to the secondary digital assets in the syndication library, the eligibility filters resulting in a set of eligible secondary digital assets in the syndication library and a set of ineligible secondary digital assets in the syndication library. The set of eligible secondary digital assets in the syndication library are linked with the primary photo library.

Abstract: Devices, methods, and non-transitory program storage devices are disclosed to provide for automatic cropping of images, given a requested target dimensions and/or aspect ratio, e.g., by using saliency maps to identify the parts of the image containing the most important content—and ensuring that such content is, if possible, included in a determined cropped region from the image. In particular, the devices, methods, and non-transitory program storage devices disclosed herein may: define a first region of interest (ROI) in a given image that is most essential to include in an automatically-determined cropped region; define a second ROI in the given image that would be preferable to include in the automatically-determined cropped region; and then determine a cropped region from the given image, based on the requested target dimensions and/or aspect ratio, that attempts to maximize an amount of overlap between the determined cropped region and the first and/or second ROIs.

Abstract: The mobile communications device may reduce the amount of location updates transmitted by applying algorithm-based filters. By setting a minimum distance threshold applied to a location update, the mobile communication device reduces the amount of location updates transmitted when the mobile communication device is “loitering” at a specific location. This disclosure describes a use of a minimum threshold used in loitering analysis and improvements to loitering calculations.