Abstract: Systems and methods for operating an EAS detection system. The methods comprise: detecting an Active Security Tag (“AST”) in an EAS detection zone; determining whether AST is coupled to an object identified in a list; and performing operations when a determination is made that AST is coupled to a listed object. The operations involve: accessing sensor data generated by at least one sensor device disposed on/near display equipment associated with the listed object; processing the sensor data to determine whether a person was within a defined distance range of AST during a period of time immediately preceding the detecting; concluding that a false alarm scenario exists when the sensor data indicates that a person was not within the defined distance range of AST during the period of time; and suppressing alarm issuance by the EAS detection system in response to the false alarm scenario conclusion.

Abstract: A video monitoring and analysis system detect subjects when they are entering and/or exiting from a room. The system enables a user to define a portal, such as doorway of the room. The system then monitors the movement of foreground objects in the room. Objects that appear only in the portal are classified as passing by the portal, e.g., doorway. Objects that initially appear in the portal and then are detected moving within the room are classified as having entered the room. Objects that are in the room and then disappear within the portal are classified as having exited the room. The system further has provisions for generating real-time alerts and performing forensic searches.

Abstract: Systems and methods for operating an EAS detection system. The methods comprise: detecting an Active Security Tag (“AST”) in an EAS detection zone; determining whether AST is coupled to an object identified in a list; and performing operations when a determination is made that AST is coupled to a listed object. The operations involve: accessing sensor data generated by at least one sensor device disposed on/near display equipment associated with the listed object; processing the sensor data to determine whether a person was within a defined distance range of AST during a period of time immediately preceding the detecting; concluding that a false alarm scenario exists when the sensor data indicates that a person was not within the defined distance range of AST during the period of time; and suppressing alarm issuance by the EAS detection system in response to the false alarm scenario conclusion.

Abstract: A system and method for identification and suppression of time varying background objects is disclosed. A proposed surveillance security system includes an image analytics system and at least one surveillance camera. The image analytics system identifies objects within image data of a scene captured by the surveillance camera, and then analyzes the objects to determine whether each object is a foreground object or a dynamic background object. In examples, the image analytics system determines whether an object is a foreground object or a dynamic background object based upon movement and/or an appearance of the object. The surveillance security system does not send alerts to users of the system for objects determined to be dynamic background objects. When users request objects of interest, the dynamic background objects are also excluded from lists of objects sent in reply messages to the users.

Abstract: Systems and methods for operating an EAS detection system. The methods comprise: detecting an Active Security Tag (“AST”) in an EAS detection zone; determining whether AST is coupled to an object identified in a list; and performing operations when a determination is made that AST is coupled to a listed object. The operations involve: accessing sensor data generated by at least one sensor device disposed on/near display equipment associated with the listed object; processing the sensor data to determine whether a person was within a defined distance range of AST during a period of time immediately preceding the detecting; concluding that a false alarm scenario exists when the sensor data indicates that a person was not within the defined distance range of AST during the period of time; and suppressing alarm issuance by the EAS detection system in response to the false alarm scenario conclusion.

Abstract: Systems and methods for operating an EAS detection system. The methods comprise: detecting an Active Security Tag (“AST”) in an EAS detection zone; determining whether AST is coupled to an object identified in a list; and performing operations when a determination is made that AST is coupled to a listed object. The operations involve: accessing sensor data generated by at least one sensor device disposed on/near display equipment associated with the listed object; processing the sensor data to determine whether a person was within a defined distance range of AST during a period of time immediately preceding the detecting; concluding that a false alarm scenario exists when the sensor data indicates that a person was not within the defined distance range of AST during the period of time; and suppressing alarm issuance by the EAS detection system in response to the false alarm scenario conclusion.

Abstract: A system and method for automated operation of a camera system provides for a positioning system that moves the camera system to a field of view to search for objects or events of interest to track. If objects or events of interest are detected prior to the expiration of a dwell timer, the dwell timer is interrupted and tracking of the objects or events of interest is initiated. To prevent the security camera from being distracted indefinitely by unimportant objects, the positioning system changes the field of view of the security system upon expiration of a track timer. Alternatively, if the security camera does not identify an object to track prior to expiration of a dwell timer, then the positioning system changes the field of view of the camera system to search for other objects or events of interest.

Abstract: A system and method for identification and suppression of time varying background objects is disclosed. A proposed surveillance security system includes an image analytics system and at least one surveillance camera. The image analytics system identifies objects within image data of a scene captured by the surveillance camera, and then analyzes the objects to determine whether each object is a foreground object or a dynamic background object. In examples, the image analytics system determines whether an object is a foreground object or a dynamic background object based upon movement and/or an appearance of the object. The surveillance security system does not send alerts to users of the system for objects determined to be dynamic background objects. When users request objects of interest, the dynamic background objects are also excluded from lists of objects sent in reply messages to the users.

Abstract: A system and method for identification and suppression of time varying background objects is disclosed. A proposed surveillance security system includes an image analytics system and at least one surveillance camera. The image analytics system identifies objects within image data of a scene captured by the surveillance camera, and then analyzes the objects to determine whether each object is a foreground object or a dynamic background object. In examples, the image analytics system determines whether an object is a foreground object or a dynamic background object based upon movement and/or an appearance of the object. The surveillance security system does not send alerts to users of the system for objects determined to be dynamic background objects. When users request objects of interest, the dynamic background objects are also excluded from lists of objects sent in reply messages to the users.

Abstract: A system and method for identification and suppression of time varying background objects is disclosed. A proposed surveillance security system includes an image analytics system and at least one surveillance camera. The image analytics system identifies objects within image data of a scene captured by the surveillance camera, and then analyzes the objects to determine whether each object is a foreground object or a dynamic background object. In examples, the image analytics system determines whether an object is a foreground object or a dynamic background object based upon movement and/or an appearance of the object. The surveillance security system does not send alerts to users of the system for objects determined to be dynamic background objects. When users request objects of interest, the dynamic background objects are also excluded from lists of objects sent in reply messages to the users.

Abstract: A system and method for automated operation of a camera system is disclosed. A positioning system moves the camera system to a field of view to search for objects or events of interest to track. If objects or events of interest are detected prior to the expiration of a dwell timer, the dwell timer is interrupted and tracking of the objects or events of interest is initiated. To prevent the security camera from being distracted indefinitely by unimportant objects, the positioning system changes the field of view of the security system upon expiration of a track timer. Alternatively, if the security camera does not identify an object to track prior to expiration of a dwell timer, then the positioning system changes the field of view of the camera system to search for other objects or events of interest.

Abstract: A system and method for automated operation of a camera system is disclosed. A positioning system moves the camera system to a field of view to search for objects or events of interest to track. If objects or events of interest are detected prior to the expiration of a dwell timer, the dwell timer is interrupted and tracking of the objects or events of interest is initiated. To prevent the security camera from being distracted indefinitely by unimportant objects, the positioning system changes the field of view of the security system upon expiration of a track timer. Alternatively, if the security camera does not identify an object to track prior to expiration of a dwell timer, then the positioning system changes the field of view of the camera system to search for other objects or events of interest.

Abstract: A method and system for analyzing video data in a security system. An analysis compares a current frame to a background model. The analysis system compares the background model to the current frame to identify changed pixel patches. The analysis system uses morphological image processing to generate masks based on the changed pixel patches. Next, the analysis system applies the masks to the background model and the current frames to determine whether the changed pixel patches are characteristic of abandoned or removed objects within the video data.

Abstract: A system and method for analyzing queues in frames of video enables operators to preferably draw three regions of interest overlaid upon the video as short, medium, and long queue regions that form a notional queue area within the video. The regions are drawn with knowledge of, or in anticipation of, foreground objects such as individuals and vehicles waiting for service in a queue. Examples include retail point of sale locations or for automated teller machine (ATM) transactions. In conjunction with a video analytics system that analyzes the movement of the foreground objects relative to the queue regions, the system determines the number of objects occupying each queue region, length of the queue, and other queue-related statistics. The system can then create reports and send messages that include the queue analysis results for directing operators to change their staffing resources as part of a real-time queue servicing and optimization response.

Abstract: An analytical device is disclosed that analyzes whether a first image is similar to (or the same as) as a second image. The analytical device analyzes the first image by combining at least a part (or all) of the first image with at least a part (or all) of the second image, and by analyzing at least a part (or all) of the combined image. Part or all of the combination may be analyzed with respect to the abstraction of the first image and/or the abstraction of the second image. The abstraction may be based on a Bag of Features (BoF) description, based on a histogram of intensity values, or based on other types of abstraction methodologies. The analysis may involve comparing one or more aspects of the combination (such as the entropy or randomness of the combination) with the one or more aspects of the abstracted first image and/or abstracted second image. Based on the comparison, the analytical device may determine whether the first image is similar to or the same as the second image.

Abstract: An analytical device is disclosed that analyzes whether a first image is similar to (or the same as) as a second image. The analytical device analyzes the first image by combining at least a part (or all) of the first image with at least a part (or all) of the second image, and by analyzing at least a part (or all) of the combined image. Part or all of the combination may be analyzed with respect to the abstraction of the first image and/or the abstraction of the second image. The abstraction may be based on a Bag of Features (BoF) description, based on a histogram of intensity values, or based on other types of abstraction methodologies. The analysis may involve comparing one or more aspects of the combination (such as the entropy or randomness of the combination) with the one or more aspects of the abstracted first image and/or abstracted second image. Based on the comparison, the analytical device may determine whether the first image is similar to or the same as the second image.

Abstract: A system and method for analysing queues in frames of video enables operators to preferably draw three regions of interest overlaid upon the video as short, medium, and long queue regions that form a notional queue area within the video. The regions are drawn with knowledge of, or in anticipation of, foreground objects such as individuals and vehicles waiting for service in a queue. Examples include retail point of sale locations or for automated teller machine (ATM) transactions. In conjunction with a video analytics system that analyses the movement of the foreground objects relative to the queue regions, the system determines the number of objects occupying each queue region, length of the queue, and other queue-related statistics. The system can then create reports and send messages that include the queue analysis results for directing operators to change their staffing resources as part of a real-time queue servicing and optimization response.

Abstract: A method and system for analyzing video data in a security system. An analysis compares a current frame to a background model. The analysis system compares the background model to the current frame to identify changed pixel patches. The analysis system uses morphological image processing to generate masks based on the changed pixel patches. Next, the analysis system applies the masks to the background model and the current frames to determine whether the changed pixel patches are characteristic of abandoned or removed objects within the video data.

Abstract: A system and method for automated operation of a camera system is disclosed. A positioning system moves the camera system to a field of view to search for objects or events of interest to track. If objects or events of interest are detected prior to the expiration of a dwell timer, the dwell timer is interrupted and tracking of the objects or events of interest is initiated. To prevent the security camera from being distracted indefinitely by unimportant objects, the positioning system changes the field of view of the security system upon expiration of a track timer. Alternatively, if the security camera does not identify an object to track prior to expiration of a dwell timer, then the positioning system changes the field of view of the camera system to search for other objects or events of interest.

Abstract: A method and system for analyzing video data in a security system. An analysis compares a current frame to a background model. The analysis system compares the background model to the current frame to identify changed pixel patches. The analysis system uses morphological image processing to generate masks based on the changed pixel patches. Next, the analysis system applies the masks to the background model and the current frames to determine whether the changed pixel patches are characteristic of abandoned or removed objects within the video data.