Abstract: A system and method is disclosed for using object recognition/verification and weight information to confirm the accuracy of a UPC scan, or to provide an affirmative recognition where no UPC scan was made.

Abstract: A system and method for detecting fraudulent identification tags, such as Universal Product Codes (UPC) applied to goods to be purchased is disclosed. Images of the goods to be purchased and corresponding feature models are stored in a database. When a customer desires to purchase an item containing a UPC, a scanned image of the item about to be purchased may be acquired and a feature model of the scanned image may be created. The system may retrieve from the database the image and feature model previously stored for the item associated with the just-scanned UPC. A variety of image processing techniques may be used to compare the scanned and database images and/or the scanned and database feature models. In one embodiment, these image processing techniques may include determining a geometric transformation that maps the features of the scanned image onto the features of a database model.

Abstract: A system and method is disclosed for using object recognition/verification and weight information to confirm the accuracy of a UPC scan, or to provide an affirmative recognition where no UPC scan was made.

Abstract: The present invention teaches and discloses method and apparatus for alerting a grocery store check out cashier of merchandise placed on the bottom tray of a typical grocery shopping cart. A passive RFID transponder is incorporated into the structure of the cart which when interrogated by an associated reader, located at the cashier's check out station, responds with a signal verifying the presence, or absence, of an unseen item upon the carts bottom tray.

Abstract: A system and method is disclosed for using object recognition/verification and weight information to confirm the accuracy of a UPC scan, or to provide an affirmative recognition where no UPC scan was made.

Abstract: Systems and methods for recognizing and identifying items located on the lower shelf of a shopping cart in a checkout lane of a retail store environment for the purpose of reducing or preventing loss or fraud and increasing the efficiency of a checkout process. The system includes one or more visual sensors that can take images of items and a computer system that receives the images from the one or more visual sensors and automatically identifies the items. The system can be trained to recognize the items using images taken of the items. The system relies on matching visual features from training images to match against features extracted from images taken at the checkout lane. Using the scale-invariant feature transformation (SIFT) method, for example, the system can compare the visual features of the images to the features stored in a database to find one or more matches, where the found one or more matches are used to identify the items.

Abstract: Disclosed is a system and method for using optical flow to detect objects moving past a camera and to select images of the moving objects. A shopping cart, for example, may be detected by subdividing an image into a plurality of image blocks; comparing the blocks to a preceding image to determine the motion of the portion of the object pictured; associating the most common motion with the shopping cart. The motion of the cart may also be integrated over time for purposes of tracking cart motion and selecting a subset of the captured images for object recognition processing. Detection of the cart and image selection improves computational efficiency an increase merchandise throughput.

Abstract: Methods and computer readable media for recognizing and identifying items located on the belt of a counter and/or in a shopping cart of a store environment for the purpose of reducing/preventing bottom-of-the-basket loss, checking out the items automatically, reducing the checkout time, preventing consumer fraud, increasing revenue and replacing a conventional UPC scanning system to enhance the checking out speed. The images of the items taken by visual sensors may be analyzed to extract features using the scale-invariant feature-transformation (SIFT) method. Then, the extracted features are compared to those of trained images stored in a database to find a set of matches. Based on the set of matches, the items are recognized and associated with one or more instructions, commands or actions without the need for personnel to visually see the items, such as by having to come out from behind a check out counter or peering over a check out counter.

Abstract: The present invention teaches and discloses method and apparatus for alerting a grocery store check out cashier of merchandise placed on the bottom tray of a typical grocery shopping cart. A passive RFID transponder is incorporated into the structure of the cart which when interrogated by an associated reader, located at the cashier's check out station, responds with a signal verifying the presence, or absence, of an unseen item upon the carts bottom tray.

Abstract: Systems and methods for recognizing and identifying items located on the lower shelf of a shopping cart in a checkout lane of a retail store environment for the purpose of reducing or preventing loss or fraud and increasing the efficiency of a checkout process. The system includes one or more visual sensors that can take images of items and a computer system that receives the images from the one or more visual sensors and automatically identifies the items. The system can be trained to recognize the items using images taken of the items. The system relies on matching visual features from training images to match against features extracted from images taken at the checkout lane. Using the scale-invariant feature transformation (SIFT) method, for example, the system can compare the visual features of the images to the features stored in a database to find one or more matches, where the found one or more matches are used to identify the items.