Abstract: A system for monitoring shopping baskets (e.g., baskets on human-propelled carts, motorized carts, or hand-carried baskets) can include a computer vision unit that can image a surveillance region (e.g., an exit to a store), determine whether a basket is empty or loaded with merchandise, and assess a potential for theft of the merchandise. The computer vision unit can include a camera and an image processor programmed to execute a computer vision algorithm to identify shopping baskets and determine a load status of the basket. The computer vision algorithm can comprise a neural network. The system can identify an at least partially loaded shopping basket that is exiting the store, without indicia of having paid for the merchandise, and execute an anti-theft action, e.g., actuating an alarm, notifying store personnel, activating a store surveillance system, activating an anti-theft device associated with the basket (e.g., a locking shopping cart wheel), etc.

Abstract: Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Various techniques utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources.

Abstract: Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Various techniques utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources.

Abstract: Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Various techniques utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources.

Abstract: A system for monitoring shopping baskets (e.g., baskets on human-propelled carts, motorized carts, or hand-carried baskets) can include a computer vision unit that can image a surveillance region (e.g., an exit to a store), determine whether a basket is empty or loaded with merchandise, and assess a potential for theft of the merchandise. The computer vision unit can include a camera and an image processor programmed to execute a computer vision algorithm to identify shopping baskets and determine a load status of the basket. The computer vision algorithm can comprise a neural network. The system can identify an at least partially loaded shopping basket that is exiting the store, without indicia of having paid for the merchandise, and execute an anti-theft action, e.g., actuating an alarm, notifying store personnel, activating a store surveillance system, activating an anti-theft device associated with the basket (e.g., a locking shopping cart wheel), etc.

Abstract: Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Various techniques utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources.

Abstract: Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Various techniques utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources.

Abstract: Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Various techniques utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources.

Abstract: A system ensures payment for the purchase of merchandise carried through a checkout aisle on the lower tray of a shopping cart. For that purpose, the system includes a controller with an embedded program for identifying a virtual structure substantially equivalent to the physical structure of the tray. Further, the system includes a sensor that determines when a cart is positioned at the checkout aisle. The system also includes a camera for creating an image of the physical structure of the tray and transmitting the image to the controller. The controller includes a means for activating the embedded program to compare the image with the virtual structure. As a result of the comparison, the controller determines whether merchandise is on the physical structure of the tray. During the comparison, the controller removes the virtual structure from the image.

Abstract: A system prevents non-payment for goods carried through a checkout aisle in a shopping cart. In the system, a scale determines the end-weight of the cart after all goods are presumably removed. Further, a controller compares the end-weight and the tare weight of the cart. When theft is suspected, a camera captures an image of the cart while an indicator at the checkout location alerts the cashier to inspect the cart for unremoved goods. Specifically, the controller creates a signal when the end-weight exceeds the tare weight to instruct the camera to capture the image and to activate the indicator to alert the cashier. The controller may include or be integrated into a network accessible by store management or outside security advisors to examine the performance of cashiers and to determine possible patterns or profiles for theft.

Abstract: A merchandise monitoring system includes a weight sensor mounted on a pad for supporting merchandise. Further, a controller is electronically connected to the weight sensor for measuring weight decrements as merchandise is removed from the pad. Also, an enunciator is mounted on the controller to create an alarm when a cumulative weight decrement exceeds a predetermined value within a pre-selected time duration. Accordingly, a mobile corresponder is carried by store personnel for receiving the alarm. To provide oversight for system operation, the controller is electrically connected to a monitor.

Abstract: A system and method for preventing push-out theft includes a network of electronic devices that are collectively operable in either a “safe restart” mode” or in an “operational” mode. The network is installed in a shopping area and prevents shopping cart removal from the area when in the “operational” mode. It does this by initially issuing egress permits to every shopping cart. The network then selectively removes egress permits when a shopping cart enters a selected section of the shopping area. Another egress permit is issued when the shopping cart successfully passes a cashier location. Otherwise, a sentry beacon will disable a shopping cart with no egress permit, before it can leave the shopping area. The network defaults to a permit issuing mode whenever a component of the system becomes inoperable.