Abstract: Target region filling techniques are described. Techniques are described in which stereo consistency is promoted between target regions, such as by sharing information during computation. Techniques are also described in which target regions of respective disparity maps are completed to promote consistency between the disparity maps. This estimated disparity may then be used as a guide to completion of a missing texture in the target region. Techniques are further described in which cross-image searching and matching is employed by leveraging a plurality of images. This may including giving preference to matches with cross-image consistency to promote consistency, thereby enforcing stereo consistency between stereo images when applicable.

Abstract: Image zooming is described. In one or more implementations, zoomed croppings of an image are scored. The scores calculated for the zoomed croppings are indicative of a zoomed cropping's inclusion of content that is captured in the image. For example, the scores are indicative of a degree to which a zoomed cropping includes salient content of the image, a degree to which the salient content included in the zoomed cropping is centered in the image, and a degree to which the zoomed cropping preserves specified regions-to-keep and excludes specified regions-to-remove. Based on the scores, at least one zoomed cropping may be chosen to effectuate a zooming of the image. Accordingly, the image may be zoomed according to the zoomed cropping such that an amount the image is zoomed corresponds to a scale of the zoomed cropping.

Abstract: Image cropping suggestion using multiple saliency maps is described. In one or more implementations, component scores, indicative of visual characteristics established for visually-pleasing croppings, are computed for candidate image croppings using multiple different saliency maps. The visual characteristics on which a candidate image cropping is scored may be indicative of its composition quality, an extent to which it preserves content appearing in the scene, and a simplicity of its boundary. Based on the component scores, the croppings may be ranked with regard to each of the visual characteristics. The rankings may be used to cluster the candidate croppings into groups of similar croppings, such that croppings in a group are different by less than a threshold amount and croppings in different groups are different by at least the threshold amount. Based on the clustering, croppings may then be chosen, e.g., to present them to a user for selection.

Abstract: Saliency map computation is described. In one or more implementations, a base saliency map is generated for an image of a scene. The base saliency map may be generated from intermediate saliency maps computed for boundary regions of the image. Each of the intermediate saliency maps may represent visual saliency of portions of the scene that are captured in the corresponding boundary region. The boundary regions may include, for instance, a top boundary region, a bottom boundary region, a left boundary region, and a right boundary region. Further, the intermediate saliency maps may be combined in such a way that an effect of a foreground object on the saliency map is suppressed. The foreground objects for which the effect is suppressed are those that occupy a majority of one of the boundary regions.

Abstract: Combined selection tool techniques are described in which selection of portions within an image is enabled via a tool configured to selectively switch between a coarse selection mode and a refinement selection mode. In one or more implementations, an image is exposed for editing in a user interface and input is obtained to select portions of the image using the tool. The selection mode is automatically toggled between the coarse selection mode and refinement selection mode based on characteristics of the input, such as position and velocity of the input or gestures mapped to the input. Then, selection boundaries defining the selection of portions of the image are modified in accordance with the input. In one approach, the coarse selection mode corresponds to a graph cut mechanism and the refinement selection mode corresponds to a level set mechanism.

Abstract: Belief propagation and affinity measure techniques are described. In one or more implementations, beliefs may be formed to solve a labeling problem for a node, such as to perform image processing. An affinity measure may be calculated that describes how similar the node is to another node. This affinity measure may then be used as a basis to determine whether the share the belief formed for the node with the other node to solve a labeling problem for the other node.

Abstract: Stereo correspondence smoothness tool techniques are described. In one or more implementations, an indication is received of a user-defined region in at least one of a plurality of stereoscopic images of an image scene. Stereo correspondence is calculated of image data of the plurality of stereoscopic images of the image scene, the calculation performed based at least in part on the user-defined region as indicating a smoothness in disparities to be calculated for pixels in the user-defined region.

Abstract: Depth map stereo correspondence techniques are described. In one or more implementations, a depth map generated through use of a depth sensor is leveraged as part of processing of stereo images to assist in identifying which parts of stereo images correspond to each other. For example, the depth map may be utilized to describe depth of an image scene which may be used as part of a stereo correspondence calculation. The depth map may also be utilized as part of a determination of a search range to be employed as part of the stereo correspondence calculation.

Abstract: Embodiments of methods and systems for stereo-aware image editing are described. A three-dimensional model of a stereo scene is built from one or more input images. Camera parameters for the input images are computed. The three-dimensional model is modified. In some embodiments, the modifying the three-dimensional model includes modifying one or more of the images and applying results of the modifying one or more of the images to corresponding model vertices. The scene is re-rendered from the camera parameters to produce an edited stereo pair that is consistent with the three-dimensional model.

Abstract: Disclosed are various embodiments labeling objects using multi-scale partitioning, rare class expansion, and/or spatial context techniques. An input image may be partitioned using different scale values to produce a different set of superpixels for each of the different scale values. Potential object labels for superpixels in each different set of superpixels of the input image may be assessed by comparing descriptors of the superpixels in each different set of superpixels of the input image with descriptors of reference superpixels in labeled reference images. An object label may then be assigned for a pixel of the input image based at least in part on the assessing of the potential object labels.

Abstract: Image matting and alpha value techniques are described. In one or more implementations, techniques are described in which matting operations are applied to image data that is in a raw or substantially raw image format. This may be used to decompose image data into foreground and background images as well as to generate an alpha value that describes a linear combination of the foreground and background images for a respective pixel. Further, implementations are also described in which a plurality of alpha values is generated for each of a plurality of pixels. These alpha values may be utilized to support a variety of different functionality, such as matting operations and so on.

Abstract: Target region fill techniques involving transformations are described. In one or more implementations, a patch to be used to fill a target region in an image of an scene is identified. A transformation to be applied to the patch is guided using depth information of the scene and at least a portion of the target region in the image is filled using the transformed patch.

Abstract: A land mine simulator includes a housing having an opening formed in one end thereof. A plate movably supported in the housing's opening has a first face exposed to a surrounding environment and a second face exposed to an interior region of the housing. A non-compressible fluid-filled reservoir in the housing includes a flexible diaphragm opposing and spaced apart from the second face of the plate. Plungers are between each of the second face of the plate and the diaphragm. Each of one or more air spring in the housing includes a cylinder having a movable piston sealed therein with a first side of the piston in fluid communication with the reservoir's fluid and a second side of the piston in fluid communication with a pressurized volume of gas within the cylinder. A pressure sensor is provided in communication with the fluid in the reservoir.

Abstract: Methods and apparatus for disparity map correction through statistical analysis on local neighborhoods. A disparity map correction technique may be used to correct mistakes in a disparity or depth map. The disparity map correction technique may detect and mark invalid pixel pairs in a disparity map, segment the image, and perform a statistical analysis of the disparities in each segment to identify outliers. The invalid and outlier pixels may then be corrected using other disparity values in the local neighborhood. Multiple iterations of the disparity map correction technique may be performed to further improve the output disparity map.

Abstract: Target region filling techniques are described. Techniques are described in which stereo consistency is promoted between target regions, such as by sharing information during computation. Techniques are also described in which target regions of respective disparity maps are completed to promote consistency between the disparity maps. This estimated disparity may then be used as a guide to completion of a missing texture in the target region. Techniques are further described in which cross-image searching and matching is employed by leveraging a plurality of images. This may including giving preference to matches with cross-image consistency to promote consistency, thereby enforcing stereo consistency between stereo images when applicable.

Abstract: Stereoscopic target region filling techniques are described. Techniques are described in which stereo consistency is promoted between target regions, such as by sharing information during computation. Techniques are also described in which target regions of respective disparity maps are completed to promote consistency between the disparity maps. This estimated disparity may then be used as a guide to completion of a missing texture in the target region. Techniques are further described in which cross-image searching and matching is employed by leveraging a plurality of images. This may including giving preference to matches with cross-image consistency to promote consistency, thereby enforcing stereo consistency between stereo images when applicable.

Abstract: Belief propagation and affinity measure techniques are described. In one or more implementations, beliefs may be formed to solve a labeling problem for a node, such as to perform image processing. An affinity measure may be calculated that describes how similar the node is to another node. This affinity measure may then be used as a basis to determine whether the share the belief formed for the node with the other node to solve a labeling problem for the other node.

Abstract: Stereo correspondence smoothness tool techniques are described. In one or more implementations, an indication is received of a user-defined region in at least one of a plurality of stereoscopic images of an image scene. Stereo correspondence is calculated of image data of the plurality of stereoscopic images of the image scene, the calculation performed based at least in part on the user-defined region as indicating a smoothness in disparities to be calculated for pixels in the user-defined region.

Abstract: Stereo correspondence model fitting techniques are described. In one or more implementations, a model may be fit to a region in at least one of a plurality of stereoscopic images of an image scene. The model may then be used as part of a stereo correspondence calculation, which may include computing disparities for the region based at least in part on correspondence to the model.

Abstract: Stereo correspondence and depth sensor techniques are described. In one or more implementations, a depth map generated by a depth sensor is leveraged as part of processing of stereo images to assist in identifying which parts of stereo images correspond to each other. The depth map, for instance, may be utilized to assist in identifying depth discontinuities in the stereo images. Additionally, techniques may be employed to align the depth discontinuities identified from the depth map to image edges identified from the stereo images. Techniques may also be employed to suppress image edges that do not correspond to the depth discontinuities of the depth map in comparison with image edges that do correspond to the depth discontinuities as part of the identification.