Abstract: A method and system is provided for predicting at a current time “t”, a time that may be taken to travel between plurality of locations, at a future time-point “t+?”. The method includes determining deterministic component “?t+?” and predicting random fluctuation component “ylt+?”, of the time that may be taken to travel between the plurality of locations at the future time-point “t+?”. The deterministic component “?t+?” and the random fluctuation component “ylt+?” are added to predict the time that may be taken to travel between the plurality of locations, at the future time-point “t+?”.

Abstract: The present disclosure includes a system in which a video displayer, having access to video surveillance data and point-of-sale transaction data, provides random-access review of point-of-sale transactional video. Embodiments herein provide a new method of reviewing security video of a transaction taking place at a retail establishment's point-of-sale transaction area, or register. Embodiments herein enable random and instantaneous access to any number of transaction events that may be of interest to a loss prevention investigator. In one embodiment, a video displayer obtains video data comprising a point-of-sale transaction occurring at a point-of-sale transaction area, and transaction data from a point-of-sale terminal. The video displayer displays video of individual transaction events from a larger transaction, and visually modifies displayed video at a moment in the video when a transaction event occurs.

Abstract: Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area. The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.

Abstract: Techniques disclosed herein include a reviewer interface for providing random-access review of point-of-sale (POS) video, visual indicators to point to point to objects within the point-of-sale video, and/or display of interactive statistical features. The system obtains video data of point-of-sale transactions, and corresponding transaction data correlated with the video data. The system identifies and displays transaction events of interest. In one embodiment, such a display includes displaying a visual indicator positioned at a spatial location within displayed video to identify a location of an object in the displayed video that corresponds to the transaction event identified as a transaction event of interest. The system also includes functionality to display visual indicators associated with transaction data to convey magnitude or quantity of transaction events of interest.

Abstract: According to one configuration, a computer environment includes a first monitoring system, a second monitoring system, and an analyzer. The first monitoring system produces video of an item being entered into a point of sale system. The second monitoring system monitors events associated with entering of the item into the point of sale system. The analyzer detects, via a communication from the second monitoring system, an occurrence of at least one event associated with entering of the item. Based on communication, the analyzer correlates the at least one event to a particular time in the video when the at least one event occurred.

Abstract: A system performs video identification of items involved with transactions, as captured in video data, and compares this item identification information with transaction data obtained from a transaction terminal such as a point-of-sale register to identify situations that are suspicious and may indicate fraudulent activity or operator error. In particular, the system as disclosed herein utilizes unique camera positions, and can use video data from more than one camera, to perform robust detections of fraudulent or suspicious activities associated with transactions in the transaction area. By obtaining video data originating from at least one video camera that monitors a transaction area, the system can automatically (i.e. no human involvement needed) analyze the video data to track items involved in a transaction in the transaction area.

Abstract: Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area. The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.

Abstract: Disclosed is a method and apparatus for allocating a set of frequency bands to a plurality of access points. The method includes generating an interference map associated with the set of frequency bands and associated with the plurality of access points. The method includes aggregating a plurality of demands to produce an aggregate demand. Each of the plurality of demands associated with one of the plurality of access points. The method includes dynamically allocating the set of frequency bands to each of the plurality of access points based on the interference map and the aggregate demand.

Abstract: Disclosed is a method and apparatus for allocating a whitespace spectrum associated with a plurality of access points. The method includes reporting a signal strength associated with each of a plurality of other access points to a central controller. The method includes aggregating a plurality of demands to produce an aggregate demand. Each of the plurality of demands is associated with one of a plurality of users. The method includes reporting the aggregated demand to the central controller. The method includes associating one of the plurality of users with the access point based on a user setting or associating one of the plurality of users based on an allocation by the central controller. The allocation from the central controller is based on the signal strength and the aggregated demand. The allocation indicates a frequency band from the set of frequency bands to be allocated by the access point to the user.

Abstract: A method and system for increasing accuracy in estimating average time taken to travel through a chosen road segment is provided. The method includes determination of time taken by one or more vehicles to travel through the road segments. Further, correlated road segments for which time taken to travel through the correlated road segments is correlated with the time taken to travel through the chosen road segment, are identified. A data repository stores a list of the one or more correlated road segments. Among the correlated road segments, one or more preferred road segments that increases the accuracy in determining the average time taken to travel through the chosen road segment, is determined by at least one processor. Further, the processor estimates the average time taken to travel through the chosen road segment using, data corresponding to time taken to travel through, the preferred road segments and the chosen road segment.

Abstract: Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area. The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.

Abstract: A method and system is provided for predicting at a current time “t”, a time that may be taken to travel between plurality of locations, at a future time-point “t+?”. The method includes determining deterministic component “?t+?” and predicting random fluctuation component “y1t+?”, of the time that may be taken to travel between the plurality of locations at the future time-point “t+?”. The deterministic component “?t+?” and the random fluctuation component “y1t+?” are added to predict the time that may be taken to travel between the plurality of locations, at the future time-point “t+?”.

Abstract: The present invention relates to a system and method for proportional-fair resource allocation for multi-rate random access. The method includes receiving, by a device, data packets to be transmitted to an access point on a shared uplink channel, and determining, by the device, whether or not to contend for access to the shared uplink channel based on a probability of access. The probability of access is based on a data transmission rate between the device and the access point.

Abstract: Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area. The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and by obtaining transaction data concerning at least one transaction that occurs at the transaction area. The system correlates the video data associated with the transaction area to the transaction data to identify specific video data captured during occurrence of that at least one transaction at the transaction area. Based a transaction classification indicated by the transaction data, the system processes the video data to identify appropriate visual indicators within the video data that correspond to the transaction classification.

Abstract: Disclosed is a method and apparatus for allocating a whitespace spectrum associated with a plurality of access points. The method includes reporting a signal strength associated with each of a plurality of other access points to a central controller. The method includes aggregating a plurality of demands to produce an aggregate demand. Each of the plurality of demands is associated with one of a plurality of users. The method includes reporting the aggregated demand to the central controller. The method includes associating one of the plurality of users with the access point based on a user setting or associating one of the plurality of users based on an allocation by the central controller. The allocation from the central controller is based on the signal strength and the aggregated demand. The allocation indicates a frequency band from the set of frequency bands to be allocated by the access point to the user.

Abstract: Disclosed is a method and apparatus for allocating a set of frequency bands to a plurality of access points. The method includes generating an interference map associated with the set of frequency bands and associated with the plurality of access points. The method includes aggregating a plurality of demands to produce an aggregate demand. Each of the plurality of demands associated with one of the plurality of access points. The method includes dynamically allocating the set of frequency bands to each of the plurality of access points based on the interference map and the aggregate demand.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.