Abstract: Examples enable pallet tag tracking and cluster voting for more accurate pallet tag management using images of a selected pallet. A tag manager tracks a pallet through multiple images of the pallet to ensure the same pallet appears in every image. If the pallet tag is absent from all the images, a tag missing confidence score is generated that indicates the degree of confidence that the tag is missing from the pallet and not merely out of view. The score is used to prioritize handling of pallet tag missing exceptions. If the pallet tag is present in the images, optical character recognition (OCR) results for each tag image are aggregated into a tag cluster with a confidence score calculated for each result. A pallet tag identification (ID) number is predicted based on the result having the highest confidence score to ensure the pallet tag ID is complete and accurate.

Abstract: Examples provide a system for enhanced pallet label checking using computer vision and optical character recognition for faster and more efficient resolution of pallet label exceptions. The system includes a pallet manager component that obtains images of pallets from one or more image capture devices. Computer vision and machine learning is utilized to identify pallet labels on pallets which are missing or damaged such that the pallet labels are at least partially unreadable. An initial pallet label exception is created. The exceptions are assigned scores indicating a degree of confidence that the exceptions are accurate and require attention to resolve the issues associated with each label. The exceptions having high confidence scores are enhanced with customized label check instructions and real time images of the pallets. The enhanced pallet label exceptions assist users in locating pallets and resolving issues associated with pallet labels with greater speed and accuracy.

Abstract: Examples provide for pallet classification and pallet tag text recognition. The system includes a pallet text manager that classifies a type of pallet tag based on detected lines of text in the pallet tag using a classification model. Qualified lines of text are selected from the detected lines of text based on the classification type and corresponding format of the text. Each qualified line of text is associated with a pallet attribute, such as a pallet identifier (ID), an item ID, or a date of creation of the pallet tag. Attribute values from the set of qualified lines of text are paired with location data for the current location of the pallet. The attribute values and the paired location data are saved in a pallet attribute table. The pallet attributes are used to identify the location of pallets in a retail facility with improved accuracy and efficiency.

Abstract: Examples provide a system for filtering the contents of adjacent item storage compartments from item recognition results obtained using computer vision (CV) for more accurate mapping of item locations within a retail environment. A filter manager selects a vertical member and tracks it throughout a series of images generated by an image capture device. The selected vertical member defines at least a portion of a target compartment in each image. The vertical member can be a display case door or a vertical steel bar defining the side of an item storage compartment. A set of adjacent items located on each side of the target compartment is filtered from the item recognition results. The target compartment location is determined based on a location tag of the target compartment. The items remaining after filtering are mapped to the target compartment location while reducing CV item location false positives.

Abstract: Examples provide a multi-object detection model for identifying different types of objects of interest using input images of a selected area including a plurality of objects. A multi-object detection manager identifies instances of each object type by adding indicators for identifying the different types of objects, such as, but not limited to, pallets, pallet tags, horizontal bars, vertical bars, wooden bases on pallets, and empty spaces. The indicators are provided within an overlay superimposed on the image. The indicators include text-based labels and/or non-text based color-coded indicators, such as color-coded bounding boxes. In such cases, instances of a first type of object are identified using a first indicator and instances of a second type of object are identified using a different second indicator. The labeled image including the indicators is generated to enable users to determine the locations of objects within a retail environment with greater accuracy and efficiency.

Abstract: Examples enable pallet tag tracking and cluster voting for more accurate pallet tag management using images of a selected pallet. A tag manager tracks a pallet through multiple images of the pallet to ensure the same pallet appears in every image. If the pallet tag is absent from all the images, a tag missing confidence score is generated that indicates the degree of confidence that the tag is missing from the pallet and not merely out of view. The score is used to prioritize handling of pallet tag missing exceptions. If the pallet tag is present in the images, optical character recognition (OCR) results for each tag image are aggregated into a tag cluster with a confidence score calculated for each result. A pallet tag identification (ID) number is predicted based on the result having the highest confidence score to ensure the pallet tag ID is complete and accurate.

Abstract: Examples provide for pallet classification and pallet tag text recognition. The system includes a pallet text manager that classifies a type of pallet tag based on detected lines of text in the pallet tag using a classification model. Qualified lines of text are selected from the detected lines of text based on the classification type and corresponding format of the text. Each qualified line of text is associated with a pallet attribute, such as a pallet identifier (ID), an item ID, or a date of creation of the pallet tag. Attribute values from the set of qualified lines of text are paired with location data for the current location of the pallet. The attribute values and the paired location data are saved in a pallet attribute table. The pallet attributes are used to identify the location of pallets in a retail facility with improved accuracy and efficiency.

Abstract: A system and method for global and local category-based item location recognition filtering is provided. A plurality of candidate items associated with a current location within a retail environment are filtered using a global level filter that identifies and removes items associated with an item category that is not a confirmed category for the recognized location. A local level filter analyzes item count values for the remaining candidate items to identify and remove low-count items. If any single item count is below a threshold, the low count items are removed. If all the candidate items are low count items at the item level, a count values for all candidate items in the same category are aggregated into a category-level item count value which is used to identify low count items. The low-count items are filtered out to eliminate false positives for improved accuracy and reliability of the item-to-location mapping results.

Abstract: A firearm noise suppressor attachable to the muzzle of a barrel having a longitudinal bore axis. It includes a housing with an outer wall, a forward end wall, and a rearward end wall. The rearward end wall attaches to a firearm barrel and the forward end wall includes an outlet opening aligned with the longitudinal bore axis. A blast chamber is defined at least in part by the rearward end wall, the outer wall, and a blast baffle. At least a second baffle is situated forward of the blast baffle and supported at a periphery by the outer wall. A plurality of circumferentially spaced apart helical blast vanes in the blast chamber impart a rotational flow to propellant gas.

Abstract: A firearm noise suppressor attachable to the muzzle of a barrel having a longitudinal bore axis. It includes a housing with an outer wall, a forward end wall, and a rearward end wall. The rearward end wall attaches to a firearm barrel and the forward end wall includes an outlet opening aligned with the longitudinal bore axis. A blast chamber is defined at least in part by the rearward end wall, the outer wall, and a blast baffle. At least a second baffle is situated forward of the blast baffle and supported at a periphery by the outer wall. A plurality of circumferentially spaced apart helical blast vanes in the blast chamber impart a rotational flow to propellant gas.