Abstract:
Systems and methods for improving automatic selection of keeper images from a commonly captured set of images are described. A combination of image type identification and image quality metrics may be used to identify one or more images in the set as keeper images. Image type identification may be used to categorize the captured images into, for example, three or more categories. The categories may include portrait, action, or “other.” Depending on the category identified, the images may be analyzed differently to identify keeper images. For portrait images, an operation may be used to identify the best set of faces. For action images, the set may be divided into sections such that keeper images selected from each section tell the story of the action. For the “other” category, the images may be analyzed such that those having higher quality metrics for an identified region of interest are selected.
Abstract:
Systems and methods for improving automatic selection of keeper images from a commonly captured set of images are described. A combination of image type identification and image quality metrics may be used to identify one or more images in the set as keeper images. Image type identification may be used to categorize the captured images into, for example, three or more categories. The categories may include portrait, action, or “other.” Depending on the category identified, the images may be analyzed differently to identify keeper images. For portrait images, an operation may be used to identify the best set of faces. For action images, the set may be divided into sections such that keeper images selected from each section tell the story of the action. For the “other” category, the images may be analyzed such that those having higher quality metrics for an identified region of interest are selected.
Abstract:
Systems and methods for improving automatic selection of keeper images from a commonly captured set of images are described. A combination of image type identification and image quality metrics may be used to identify one or more images in the set as keeper images. Image type identification may be used to categorize the captured images into, for example, three or more categories. The categories may include portrait, action, or “other.” Depending on the category identified, the images may be analyzed differently to identify keeper images. For portrait images, an operation may be used to identify the best set of faces. For action images, the set may be divided into sections such that keeper images selected from each section tell the story of the action. For the “other” category, the images may be analyzed such that those having higher quality metrics for an identified region of interest are selected.
Abstract:
For cameras that capture several images in a burst mode, some embodiments of the invention provide a method that presents one or more of the captured images differently than the remaining captured images. The method identifies at least one captured image as dominant image and at least another captured image as a non-dominant image. The method then displays each dominant image different from each non-dominant image in a concurrent presentation of the images captured during the burst mode. The dominant images may appear larger than non-dominant images, and/or appear with a marking that indicates that the images are dominant.
Abstract:
For cameras that capture several images in a burst mode, some embodiments of the invention provide a method that presents one or more of the captured images differently than the remaining captured images. The method identifies at least one captured image as dominant image and at least another captured image as a non-dominant image. The method then displays each dominant image different from each non-dominant image in a concurrent presentation of the images captured during the burst mode. The dominant images may appear larger than non-dominant images, and/or appear with a marking that indicates that the images are dominant.
Abstract:
In one embodiment described herein, a device having an account permitting access to network-based storage, receives a push notification indicating that one or more assets has been shared by another person. In response to the push notification, the device begins downloading the new asset to the device, while starting two timers. When the first timer finishes, the user is notified about the new asset that is available. When the second timer finishes, the download, if still in progress, is interrupted to save power.
Abstract:
In some implementations, a computing device can automatically name moments (e.g., a time-based collections of images) based on the accuracy of the location data corresponding to the captured image. The computing device can, for example, send location coordinates for an image associated with a moment to a location server. The computing device can receive a hierarchical list of location strings corresponding to the location coordinates from the location server. The computing device can filter the location strings based on an accuracy metric associated with the location coordinates for the image. The computing device can suggest or select a name for the collection of images based on the filtered location strings.
Abstract:
For cameras that capture several images in a burst mode, some embodiments of the invention provide a method that presents one or more of the captured images differently than the remaining captured images. The method identifies at least one captured image as dominant image and at least another captured image as a non-dominant image. The method then displays each dominant image different from each non-dominant image in a concurrent presentation of the images captured during the burst mode. The dominant images may appear larger than non-dominant images, and/or appear with a marking that indicates that the images are dominant.
Abstract:
For cameras that capture several images in a burst mode, some embodiments of the invention provide a method that presents one or more of the captured images differently than the remaining captured images. The method identifies at least one captured image as dominant image and at least another captured image as a non-dominant image. The method then displays each dominant image different from each non-dominant image in a concurrent presentation of the images captured during the burst mode. The dominant images may appear larger than non-dominant images, and/or appear with a marking that indicates that the images are dominant.