Zebra Technologies Corporation

Symbol Technologies, LLC

Vlad Gorodetsky

Richard Jeffrey Rzeszutek

Joseph Lam

Giorgio Gallina

Anshul V Joshi

Eliezer Azi Ben-Lavi

Qifeng Gan

A method includes obtaining a point cloud captured by a depth sensor, and image data captured by an image sensor, the point cloud and the image data representing a support structure bearing a set of objects; obtaining an image boundary corresponding to an object from the set of objects; determining a portion of the point cloud corresponding to the image boundary; selecting, from the determined portion, a subset of points corresponding to a forward surface of the object; and generating a three-dimensional position of the object based on the forward surface.

Mixed depth object detection

A method of barrier detection in an imaging controller includes: obtaining an image of a support structure configured to support a plurality of items on a support surface extending between a shelf edge and a shelf back; extracting frequency components representing pixels of the image; based on the extracted frequency components, identifying a barrier region of the image, the barrier region containing a barrier adjacent to the shelf edge; and detecting at least one empty sub-region within the barrier region, wherein the empty sub-region is free of items between the barrier and the shelf back.

Barrier detection for support structures

A method of label detection includes: obtaining, by an imaging controller, an image depicting a shelf; increasing an intensity of a foreground subset of image pixels exceeding an upper intensity threshold, and decreasing an intensity of a background subset of pixels below a lower intensity threshold; responsive to the increasing and the decreasing, (i) determining gradients for each of the pixels and (ii) selecting a candidate set of the pixels based on the gradients; overlaying a plurality of shelf candidate lines on the image derived from the candidate set of pixels; identifying a pair of the shelf candidate lines satisfying a predetermined sequence of intensity transitions; and generating and storing a shelf edge bounding box corresponding to the pair of shelf candidate lines.

Method and apparatus for shelf edge detection

A method in an imaging controller of detecting obstructions on a front of a support structure includes: obtaining (i) a point cloud of the support structure and an obstruction, and (ii) a support structure plane corresponding to the front of the support structure; for each of a plurality of selection depths: selecting a subset of points from the point cloud based on the selection depth; detecting obstruction candidates from the subset of points and, for each obstruction candidate: responsive to a dimensional criterion being met, determining whether the obstruction candidate meets a confirmation criterion; when the obstruction candidate meets the confirmation criterion, identifying the obstruction candidate as a confirmed obstruction; and presenting obstruction detection output data including the confirmed obstructions.

Method, system and apparatus for detecting support structure obstructions

A method of recovering label positions in an imaging controller includes: receiving (i) a definition of a plane containing edges of the shelf, and (ii) a plurality of initial label indicators having locations on the plane; assigning the initial label indicators among a plurality of candidate subsets each representing a single physical label; for each candidate subset of initial indicators: generating, for each of a plurality of projection depths relative to the plane, a set of projections of the initial indicators in the candidate subset; determining an aggregate surface area for each set of projections; selecting, as a recovered depth for the candidate subset, one of the projection depths corresponding to the minimum aggregate surface area; and generating a recovered position for the candidate subset based on the recovered depth; and storing the recovered positions.

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North York, Canada

Vlad Gorodetsky