Abstract: Systems and methods of detecting and recognizing products on product storage structures of a product storage facility include an image capture device that moves about and captures images of the product storage structures at the product storage facility. A computing device processes the obtained images to detect and identify the products on the product storage structure, crops each of the identified individual products from the image to generate a plurality of cropped images and generates an image histogram template, feature vector template and location information template for each of the cropped images. The cropped images are stored in an electronic database and represent a reference model for each of the identified individual products and are stored in association with the generated image histogram template, feature vector template and location information template to facilitate recognition of products subsequently captured on the product storage structure by the image capture device.

Abstract: Systems and methods of analyzing on-shelf price tag labels and products at a product storage facility include an image capture device that captures one or more images of one or more product storage structures at a product storage facility. A computing device communicatively coupled to the image capture device analyzes the images of the product storage structures captured by the image capture device and detects individual price tag labels and individual products located on the product storage structure. Based on the detection of the price tag labels and the products, the computing device also defines separate product storage spaces of the product storage structure, determines which price tag labels are allocated to which of the separate product storage spaces, and associates in a database the price tag labels allocated to the product storage spaces with the products stored in those product storage spaces.

Abstract: A transaction record is created showing a purchase transaction of a customer. A CV profile showing a list of items in the transaction obtained from images is also obtained. The items in the transaction record are compared to items on the list. When there is a discrepancy, an action to take is determined.

Abstract: There are provided systems and methods relating to checking and confirming merchandise purchased at shopping facilities. In one form, the system includes: a shopping cart containing merchandise items to be purchased; a sales transaction database; a point-of-sales system that creates transaction records identified by transaction identifiers; and a mobile device used by an employee that includes a sensor to scan a paper or digital receipt to obtain the transaction identifier and a camera to capture images of the items in the shopping cart. The system also includes a control circuit that receives the transaction identifier, accesses the database using the identifier to determine the purchased items; analyzes the images of the merchandise items in the shopping cart and creates a computer vision receipt listing detected items; compares the purchased items with the detected items; and takes an action if there is a discrepancy.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to automatically annotating images. In some embodiments, a system for automatically annotating images comprises a database, wherein the database is configured to store images and annotations for the images and a control circuit, wherein the control circuit is communicatively coupled to the database, and wherein the control circuit is configured to retrieve, from the database, an image, generate, based on the image, a collection of augmented images, generate segmentation maps for each image in the collection of augmented images, wherein each of the segmentation maps include segments, select, based on a threshold, ones of the segments above a threshold, merge the ones of the segments above the threshold to create a segmented image, and generate, for each segment of the segmented image, classifications, wherein an annotation for the image includes the segmented images and the classifications.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to detecting inbound and outbound traffic. In some embodiments, there is provided a system for detecting inbound and outbound traffic at a facility including a video camera and a control circuit configured to detect a human and estimate a location of the human; determine whether the detected human is inbound or outbound the facility based on a relative movement of the detected human within a first region, a second region, and a third region; and transmit data based on the determination.

Abstract: Systems and methods of analyzing on-shelf price tag labels and products at a product storage facility include an image capture device that captures one or more images of one or more product storage structures at a product storage facility. A computing device communicatively coupled to the image capture device analyzes the images of the product storage structures captured by the image capture device and detects individual price tag labels and individual products located on the product storage structure. Based on the detection of the price tag labels and the products, the computing device also defines separate product storage spaces of the product storage structure, determines which price tag labels are allocated to which of the separate product storage spaces, and associates in a database the price tag labels allocated to the product storage spaces with the products stored in those product storage spaces.

Abstract: A transaction record is created showing a purchase transaction of a customer. A CV profile showing a list of items in the transaction obtained from images is also obtained. The items in the transaction record are compared to items on the list. When there is a discrepancy, an action to take is determined.

Abstract: Systems and methods of monitoring inventory of a product storage facility include an image capture device configured to move about the product storage areas of the product storage facility and capture images of the product storage areas from various angles. A computing device coupled to the image capture device obtains the images of the product storage areas captured by the image capture device and processes the obtained images of the product storage areas to detect individual products captured in the obtained images. Based on detection of the individual products captured in the images, the computing device analyzes each of the obtained images to detect one or more adjacent product storage structures (shelves, pallets, etc.) and identifies and selects a single image that fully shows a product storage structure of interest and fully shows each of the products stored on the product storage structure of interest.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to detecting text in images. In some embodiments, a system for detecting text in images comprises a database configured to store images and a control circuit configured to retrieve an image, generate, based on the image, a collection of augmented images, detect characters in each of the augmented images, generate bounding boxes for the characters in each of augmented images, recognize the characters in each of the augmented images, select, based on the recognition of the characters in each of the augmented images, candidate characters, wherein the candidate characters are selected based on consistency of the recognition of the characters in each of the augmented images, detect, for the image, a color associated with the characters, and store, in the database, the image, the candidate characters, and the color associated with the characters.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to automatically annotating images. In some embodiments, a system for automatically annotating images comprises a database, wherein the database is configured to store images and annotations for the images and a control circuit, wherein the control circuit is communicatively coupled to the database, and wherein the control circuit is configured to retrieve, from the database, an image, generate, based on the image, a collection of augmented images, generate segmentation maps for each image in the collection of augmented images, wherein each of the segmentation maps include segments, select, based on a threshold, ones of the segments above a threshold, merge the ones of the segments above the threshold to create a segmented image, and generate, for each segment of the segmented image, classifications, wherein an annotation for the image includes the segmented images and the classifications.

Abstract: Some embodiments provide image evaluation systems and methods, comprising: a plurality of camera systems distributed about a retail facility and each of the plurality of camera systems; and an image processing system configured to receive multiple images over time, process each image comprising: determine, from pixel data, a gradient amplitude and directional component; determine a histogram curve from the gradient amplitudes as a function of the directional component of the pixel data, and identify a key direction relative to a maximum accumulation of the gradient amplitudes; for the gradient amplitudes, of the pixel data, having a corresponding directional component that is within a direction threshold of the key direction, identify a number of local maxima corresponding to the key direction; and determine a quantity of items of the product corresponding to a quantity of the number of local maxima.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to automatically annotating images. In some embodiments, a system for automatically annotating images comprises a database, wherein the database is configured to store images and annotations for the images and a control circuit, wherein the control circuit is communicatively coupled to the database, and wherein the control circuit is configured to retrieve, from the database, an image, generate, based on the image, a collection of augmented images, generate segmentation maps for each image in the collection of augmented images, wherein each of the segmentation maps include segments, select, based on a threshold, ones of the segments above a threshold, merge the ones of the segments above the threshold to create a segmented image, and generate, for each segment of the segmented image, classifications, wherein an annotation for the image includes the segmented images and the classifications.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to self-checkout verification at a retail facility. In some embodiments, there is provided a system for self-checkout verification at a retail facility including a first optical imaging unit; and a control circuit. The control circuit configured to: receive purchase receipt data; receive one or more images of the items in the container; and execute a machine learning model trained to: perform item detection, item classification, and item verification of each item shown in the one or more images; and output electronic data corresponding to an electronic receipt of the items in the container. The control circuit may automatically detect each unpaid item in the container based on a comparison of the purchase receipt data with the electronic data; and provide an alert signal in response to automatically detecting an unpaid item.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to detecting text in images. In some embodiments, a system for detecting text in images comprises a database configured to store images and a control circuit configured to retrieve an image, generate, based on the image, a collection of augmented images, detect characters in each of the augmented images, generate bounding boxes for the characters in each of augmented images, recognize the characters in each of the augmented images, select, based on the recognition of the characters in each of the augmented images, candidate characters, wherein the candidate characters are selected based on consistency of the recognition of the characters in each of the augmented images, detect, for the image, a color associated with the characters, and store, in the database, the image, the candidate characters, and the color associated with the characters.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to detecting text in images. In some embodiments, a system for detecting text in images comprises a database configured to store images and a control circuit configured to retrieve an image, generate, based on the image, a collection of augmented images, detect characters in each of the augmented images, generate bounding boxes for the characters in each of augmented images, recognize the characters in each of the augmented images, select, based on the recognition of the characters in each of the augmented images, candidate characters, wherein the candidate characters are selected based on consistency of the recognition of the characters in each of the augmented images, detect, for the image, a color associated with the characters, and store, in the database, the image, the candidate characters, and the color associated with the characters.

Abstract: There are provided systems and methods relating to checking and confirming merchandise purchased at shopping facilities. In one form, the system includes: a shopping cart containing merchandise items to be purchased; a sales transaction database; a point-of-sales system that creates transaction records identified by transaction identifiers; and a mobile device used by an employee that includes a sensor to scan a paper or digital receipt to obtain the transaction identifier and a camera to capture images of the items in the shopping cart. The system also includes a control circuit that receives the transaction identifier, accesses the database using the identifier to determine the purchased items; analyzes the images of the merchandise items in the shopping cart and creates a computer vision receipt listing detected items; compares the purchased items with the detected items; and takes an action if there is a discrepancy.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to detecting inbound and outbound traffic. In some embodiments, there is provided a system for detecting inbound and outbound traffic at a facility including a video camera and a control circuit configured to detect a human and estimate a location of the human; determine whether the detected human is inbound or outbound the facility based on a relative movement of the detected human within a first region, a second region, and a third region; and transmit data based on the determination.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to automatically determining location of an object. In some embodiments, there is provided a system for automatically determining location of an object inside a retail store via one or more cameras including: a plurality of locations inside a retail store; a first camera capturing a first image of a first location; a portable electronic device configured to transmit a signal used to determine an absolute location of a test object; one or more first receiver circuits configured to receive transmitted first signals from the portable electronic device; and a control circuit configured to: associate a first set of store coordinates of a first coordinate system associated with an entire area inside the retail store with a first set of frame coordinates of a second coordinate system associated with the plurality of cameras; and cause a database to store the association.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to detecting and tracking humans. In some embodiments, there is provided a system for detecting and tracking humans from one image to another image including: a camera; a control circuit configure to: receive a first image; detect a plurality of key body joints of a first human captured on the first image; determine segmentations of the plurality of key body joints to determine one or more body parts of the first human; determine a color distribution map of aggregate pixels associated with each body part of the first human on the first image; and cause a database to store the color distribution map; and a database comprising one or more color distribution map sets each associated with a detected human in a captured image of the camera.