Abstract: A method of detecting a back of a shelf for supporting objects includes: obtaining an image depicting a shelf having a shelf edge and a support surface extending from the shelf edge to a shelf back; decomposing the image into a plurality of patches; for each patch: generating a feature descriptor; based on the feature descriptor, assigning one of a shelf back classification and a non-shelf back classification to the patch; generating a mask corresponding to the image, the mask containing an indication of the classification assigned to each of the patches; and presenting the mask.

Abstract: A method of determining a support structure depth of a support structure having a front and a back separated by the support structure depth includes: obtaining a point cloud of the support structure, and a mask indicating, for a plurality of portions of an image of the support structure captured from a capture pose, respective confidence levels that the portions depict the back of the support structure; selecting, from the point cloud, an initial set of points located within a field of view originating at the capture pose; selecting, from the initial set of points, an unoccluded subset of depth measurements, the depth measurements in the unoccluded subset corresponding to respective image coordinates; retrieving, from the mask, a confidence level for each of the depth measurements in the unoccluded subset; and based on the depth measurements in the unoccluded subset and the retrieved confidence levels, determining the support structure depth.

Abstract: Techniques are described for identifying correspondences between images to generate a fundamental matrix for the camera positions related to the images. The resultant fundamental matrix enables epipolar geometry to correlate common features among the images. Correspondences are identified by confirming feature matches across images by applying a homography to data representing features across images. Further techniques are described herein for generating a representation of a boundary of a feature of a structure based on a digital image. In one or more embodiments, generating a representation of a boundary of a particular feature in a digital image comprises determining a portion of the image that corresponds to the structure, and determining a portion of the image that corresponds to the particular feature. One more vanishing points are associated with the portion of the image corresponding to the particular feature.

Abstract: A method of detecting objects on a support structure includes: obtaining a point cloud of the support structure supporting an object; obtaining a position of a back of the support structure in the point cloud; discarding a portion of the point cloud based on the position of the back of the support structure; generating a three-dimensional occupancy grid from the point cloud, the occupancy grid having a plurality of cells each indicating whether the cell is one of occupied and unoccupied; identifying a contiguous region of occupied cells in the occupancy grid corresponding to the object; and generating a detected object position based on the contiguous region.

Abstract: A method of detecting objects on a support structure includes: obtaining a point cloud of the support structure supporting an object; obtaining a position of a back of the support structure in the point cloud; discarding a portion of the point cloud based on the position of the back of the support structure; generating a three-dimensional occupancy grid from the point cloud, the occupancy grid having a plurality of cells each indicating whether the cell is one of occupied and unoccupied; identifying a contiguous region of occupied cells in the occupancy grid corresponding to the object; and generating a detected object position based on the contiguous region.

Abstract: A method of detecting a back of a shelf for supporting objects includes: obtaining an image depicting a shelf having a shelf edge and a support surface extending from the shelf edge to a shelf back; decomposing the image into a plurality of patches; for each patch: generating a feature descriptor; based on the feature descriptor, assigning one of a shelf back classification and a non-shelf back classification to the patch; generating a mask corresponding to the image, the mask containing an indication of the classification assigned to each of the patches; and presenting the mask.

Abstract: A method in an imaging controller of correcting translucency artifacts in data representing one or more objects disposed on a shelf includes: obtaining a plurality of depth measurements captured by a depth sensor and corresponding to an area containing the shelf; obtaining (i) a definition of a plane containing edges of the shelf, (ii) a location in the plane of an upper shelf edge, and (iii) a location in the plane of a lower shelf edge adjacent to the upper shelf edge; generating a depth map containing, for each of a plurality of positions in the plane, a nearest object depth; detecting an upper object boundary in the depth map between the upper and lower support surface edges; updating each nearest object depth between the upper object boundary and the lower shelf edge to contain a depth of the upper object boundary; and storing the corrected depth map.

Abstract: A method of detecting a back of a shelf for supporting objects includes: obtaining an image depicting a shelf having a shelf edge and a support surface extending from the shelf edge to a shelf back; decomposing the image into a plurality of patches; for each patch: generating a feature descriptor; based on the feature descriptor, assigning one of a shelf back classification and a non-shelf back classification to the patch; generating a mask corresponding to the image, the mask containing an indication of the classification assigned to each of the patches; and presenting the mask.

Abstract: A method of determining a support structure depth of a support structure having a front and a back separated by the support structure depth includes: obtaining a point cloud of the support structure, and a mask indicating, for a plurality of portions of an image of the support structure captured from a capture pose, respective confidence levels that the portions depict the back of the support structure; selecting, from the point cloud, an initial set of points located within a field of view originating at the capture pose; selecting, from the initial set of points, an unoccluded subset of depth measurements, the depth measurements in the unoccluded subset corresponding to respective image coordinates; retrieving, from the mask, a confidence level for each of the depth measurements in the unoccluded subset; and based on the depth measurements in the unoccluded subset and the retrieved confidence levels, determining the support structure depth.

Abstract: A method of detecting objects on a support structure includes: obtaining a point cloud of the support structure supporting an object; obtaining a position of a back of the support structure in the point cloud; discarding a portion of the point cloud based on the position of the back of the support structure; generating a three-dimensional occupancy grid from the point cloud, the occupancy grid having a plurality of cells each indicating whether the cell is one of occupied and unoccupied; identifying a contiguous region of occupied cells in the occupancy grid corresponding to the object; and generating a detected object position based on the contiguous region.

Abstract: A method in an imaging controller of correcting translucency artifacts in data representing one or more objects disposed on a shelf includes: obtaining a plurality of depth measurements captured by a depth sensor and corresponding to an area containing the shelf; obtaining (i) a definition of a plane containing edges of the shelf, (ii) a location in the plane of an upper shelf edge, and (iii) a location in the plane of a lower shelf edge adjacent to the upper shelf edge; generating a depth map containing, for each of a plurality of positions in the plane, a nearest object depth; detecting an upper object boundary in the depth map between the upper and lower support surface edges; updating each nearest object depth between the upper object boundary and the lower shelf edge to contain a depth of the upper object boundary; and storing the corrected depth map.

Abstract: A method of detecting a back of a shelf for supporting objects includes: obtaining an image depicting a shelf having a shelf edge and a support surface extending from the shelf edge to a shelf back; decomposing the image into a plurality of patches; for each patch: generating a feature descriptor; based on the feature descriptor, assigning one of a shelf back classification and a non-shelf back classification to the patch; generating a mask corresponding to the image, the mask containing an indication of the classification assigned to each of the patches; and presenting the mask.

Abstract: Certain embodiments relate to processing images by creating scale space images from an image and using them to identify boundaries of objects in the image. The scale space images can have varying levels of detail. They are used to determine a potential map, which represents a likelihood for pixels to be within or outside a boundary of an object. A label estimating an object boundary can be generated and used to identify pixels that potentially may be within the boundary. An image with object boundaries identified can be further processed before exhibition. For example, the images may be two-dimensional images of a motion picture. Object boundaries can be identified and the two-dimensional (2D) images can be processed using the identified object boundaries and converted to three-dimensional (3D) images for exhibition.

Abstract: Certain embodiments relate to processing images by creating scale space images from an image and using them to identify boundaries of objects in the image. The scale space images can have varying levels of detail. They are used to determine a potential map, which represents a likelihood for pixels to be within or outside a boundary of an object. A label estimating an object boundary can be generated and used to identify pixels that potentially may be within the boundary. An image with object boundaries identified can be further processed before exhibition. For example, the images may be two-dimensional images of a motion picture. Object boundaries can be identified and the two-dimensional (2D) images can be processed using the identified object boundaries and converted to three-dimensional (3D) images for exhibition.