Abstract:
Systems, methods, and computer readable media for adjusting the orientation of an image frame and a scene depicted in the image frame are described. In general, techniques are disclosed for analyzing an image with one or more feature detectors to identify features in the image. An alignment or position associated with one or more features identified in the image may be used to determine a proper orientation for the image frame. The image can then be rotated to the proper orientation. It may also be determined if a scene depicted in the image is properly aligned in the rotated image orientation. If not, alignment information associated with the identified features may be utilized to straighten the depicted scene.
Abstract:
Techniques are provided for efficiently generating 3D information from a set of digital images. Techniques are also provided for displaying groups (or clusters) of digital images using 3D information associated with the digital images. In one technique, a group of digital images are displayed as a stack of thumbnail images where the thumbnail images are aligned on a display with respect to each other based on common features identified in the digital images, camera position, and/or camera pose. In another technique, a group of digital images are organized on a display in either a 3D layout or a 2D layout based on 3D information associated with each digital image in the group. In another technique, a transition effect is generated based on projections of two digital images onto a common scene plane and blending (or cross fading) one of the 3D projections with the other of the 3D projections.
Abstract:
Systems, methods, and computer readable media for adjusting the orientation of an image frame and a scene depicted in the image frame are described. In general, techniques are disclosed for analyzing an image with one or more feature detectors to identify features in the image. An alignment or position associated with one or more features identified in the image may be used to determine a proper orientation for the image frame. The image can then be rotated to the proper orientation. It may also be determined if a scene depicted in the image is properly aligned in the rotated image orientation. If not, alignment information associated with the identified features may be utilized to straighten the depicted scene.
Abstract:
By providing 3D representations of noteworthy locations for comparison with images, the 3D location of the imaging device, as well as the orientation of the device may be determined. The 3D location and orientation of the imaging device then allows for enhanced navigation in a collection of images, as well as enhanced visualization and editing capabilities. The 3D representations of noteworthy locations may be provided in a database that may be stored local or remote to the imaging device or a programmable device processing images obtained from the imaging device.
Abstract:
By providing 3D representations of noteworthy locations for comparison with images, the 3D location of the imaging device, as well as the orientation of the device may be determined. The 3D location and orientation of the imaging device then allows for enhanced navigation in a collection of images, as well as enhanced visualization and editing capabilities. The 3D representations of noteworthy locations may be provided in a database that may be stored local or remote to the imaging device or a programmable device processing images obtained from the imaging device.
Abstract:
Techniques are provided for efficiently generating 3D information from a set of digital images. Techniques are also provided for displaying groups (or clusters) of digital images using 3D information associated with the digital images. In one technique, a group of digital images are displayed as a stack of thumbnail images where the thumbnail images are aligned on a display with respect to each other based on common features identified in the digital images, camera position, and/or camera pose. In another technique, a group of digital images are organized on a display in either a 3D layout or a 2D layout based on 3D information associated with each digital image in the group. In another technique, a transition effect is generated based on projections of two digital images onto a common scene plane and blending (or cross fading) one of the 3D projections with the other of the 3D projections.
Abstract:
Techniques are provided to improve the performance and accuracy of landmark point detection using a Constrained Local Model. The accuracy of feature filters used by the model may be improved by supplying positive and negative sets of image data from training image regions of varying shapes and sizes to a linear support vector machine training algorithm. The size and shape of regions within which a feature filter is to be applied may be determined based on a variance in training image data for a landmark point with which the feature filter is associated. A sample image may be normalized and a confidence map generated for each landmark point by applying the feature filters as a convolution on the normalized image. A vector flow map may be pre-computed to improve the efficiency with which a mean landmark point is adjusted toward a corresponding landmark point in a sample image.
Abstract:
The electronic device with one or more processors and memory provides a digital photograph of a real-world scene. The electronic device provides a natural language text string corresponding to a speech input associated with the digital photograph. The electronic device performs natural language processing on the text string to identify one or more terms associated with an entity, an activity, or a location. The electronic device tags the digital photograph with the one or more terms and their associated entity, activity, or location.
Abstract:
Techniques are provided to improve the performance and accuracy of landmark point detection using a Constrained Local Model. The accuracy of feature filters used by the model may be improved by supplying positive and negative sets of image data from training image regions of varying shapes and sizes to a linear support vector machine training algorithm. The size and shape of regions within which a feature filter is to be applied may be determined based on a variance in training image data for a landmark point with which the feature filter is associated. A sample image may be normalized and a confidence map generated for each landmark point by applying the feature filters as a convolution on the normalized image. A vector flow map may be pre-computed to improve the efficiency with which a mean landmark point is adjusted toward a corresponding landmark point in a sample image.
Abstract:
Techniques are provided for efficiently generating 3D information from a set of digital images. Techniques are also provided for displaying groups (or clusters) of digital images using 3D information associated with the digital images. In one technique, a group of digital images are displayed as a stack of thumbnail images where the thumbnail images are aligned on a display with respect to each other based on common features identified in the digital images, camera position, and/or camera pose. In another technique, a group of digital images are organized on a display in either a 3D layout or a 2D layout based on 3D information associated with each digital image in the group. In another technique, a transition effect is generated based on projections of two digital images onto a common scene plane and blending (or cross fading) one of the 3D projections with the other of the 3D projections.