Abstract: A system and method for the capture and storage of data relating to the movements of objects, in a specified area and enables this data to be displayed in a graphically meaningful and useful manner. Video data is collected and video metadata is generated relating to objects (persons) appearing in the video data and their movements over time. The movements of the objects are then analyzed to detect the movements within a region of interest. This detection of movement allows a user, such as a manager of a store, to make informed decisions as to the infrastructure and operation of the store. One detection method relates to the number of people that are present in a region of interest for a specified time period. A second detection method relates to the number of people that remain or dwell in a particular area for a particular time period. A third detection method determines the flow of people and the direction they take within a region of interest.

Abstract: A system and method for the capture and storage of data relating to the movements of objects, in a specified area and enables this data to be displayed in a graphically meaningful and useful manner. Video data is collected and video metadata is generated relating to objects (persons) appearing in the video data and their movements over time. The movements of the objects are then analyzed to detect the movements within a region of interest. This detection of movement allows a user, such as a manager of a store, to make informed decisions as to the infrastructure and operation of the store. One detection method relates to the number of people that are present in a region of interest for a specified time period. A second detection method relates to the number of people that remain or dwell in a particular area for a particular time period. A third detection method determines the flow of people and the direction they take within a region of interest.

Abstract: A system and method for the capture and storage of data relating to the movements of objects, in a specified area and enables this data to be displayed in a graphically meaningful and useful manner. Video data is collected and video metadata is generated relating to objects (persons) appearing in the video data and their movements over time. The movements of the objects are then analyzed to detect the movements within a region of interest. This detection of movement allows a user, such as a manager of a store, to make informed decisions as to the infrastructure and operation of the store. One detection method relates to the number of people that are present in a region of interest for a specified time period. A second detection method relates to the number of people that remain or dwell in a particular area for a particular time period. A third detection method determines the flow of people and the direction they take within a region of interest.

Abstract: A system and method for the capture and storage of data relating to the movements of objects, in a specified area and enables this data to be displayed in a graphically meaningful and useful manner. Video data is collected and video metadata is generated relating to objects (persons) appearing in the video data and their movements over time. The movements of the objects are then analyzed to detect the movements within a region of interest. This detection of movement allows a user, such as a manager of a store, to make informed decisions as to the infrastructure and operation of the store. One detection method relates to the number of people that are present in a region of interest for a specified time period. A second detection method relates to the number of people that remain or dwell in a particular area for a particular time period. A third detection method determines the flow of people and the direction they take within a region of interest.

Abstract: In order to trigger an out of focus alert when the focus level of a video frame meets a focus criteria, a method is performed including the operations of: receiving a video frame, partitioning the video frame into a plurality of blocks, calculating an array of discrete cosign transformation (DCT) coefficients for at least one of the plurality of blocks using a DCT, classifying each of the at least one of the plurality of blocks based on the array of DCT coefficients for that block, calculating a focus level of the video frame from the block classifications, and triggering an out of focus alert if the focus level meets a focus criteria.

Abstract: Systems and methods of workforce scheduling are disclosed. One example embodiment, among others, comprises a computer-implemented method of scheduling workers. Each worker is associated with one of a set of flexibility classifications, which include non-flex-time and at least one flex-time. The method includes generating a set of shift instances to cover forecasted demand over a planning period, and assigning the shift instances to the set of workers by iterating through the each of the workers to assign at least a portion of the shift instances to a selected one of the workers. The assigning is such that total hours assigned to the selected worker depends on a number associated with the classification of the selected worker.