Parcel theft deterrence for audio/video (A/V) recording and communication devices, such as video doorbells and security cameras. When an A/V recording and communication device captures image data that includes a parcel, a parcel boundary may be created for monitoring the parcel within. In various embodiments, when the parcel is removed from the parcel boundary, a user alert may be generated to notify a user of a client device associated with the A/V recording and communication device that the parcel has been removed.

An UGV 1 acquires a moving image of an captured imaging area, detects a receiver of an article on the basis of frame images forming the moving image, sets, as the monitoring area, an area including at least a part of the receiver and the area at a point in time when the receiver appears, detects a outsider entering the monitoring area or a outsider heading for the monitoring area on the basis of a frame image that is temporally later than a first frame image at the point in time when the receiver appears, and executes processing for notifying the receiver of outsider detection information.

A first camera and a second camera are installed in a facility. An analyzing apparatus detects the same person from a first captured image generated by the first camera and a second captured image generated by the second camera. The analyzing apparatus computes a movement time which is required for the detected person to move between a captured area of the first camera and a captured area of the second camera. The analyzing apparatus determines an attributed of the person using at least one of the first captured image and the second captured image. The analyzing apparatus acquires a reference value corresponding to the determined attribute, compares the computed movement time with the acquired reference value, and outputs output information based on a result of the comparison.

A computer assisted facility monitoring method provides users with predefined operating procedures that are recommended for addressing one or more alarms acknowledged by the user. The predefined operating procedures are created and stored prior to the occurrence of the alarms. In some examples, after acknowledging an alarm occurrence, the user may be provided with an option for bypassing or disregarding the alarm, as some such acknowledgements may have been for false alarms. In some examples, the predefined operating procedure may specify multiple action steps for addressing an alarm. In such examples, the user can close out or settle an alarm incident even without completing all of the action steps, provided the user enters a valid reason for doing so. In some examples, a user can batch-select a group of alarms, wherein perhaps only some of the acknowledged alarms in the group have corresponding predefined operating procedures.

An apparatus comprising a camera sensor and a processor. The camera sensor may be configured to generate video data of an area of interest. The processor may be configured to (A) analyze the video data, (B) generate control signals and (C) adjust a status of a plurality of security responses. The control signals may be generated in response to (a) the analysis of the video data and (b) the status of the security responses. The control signals may adjust an activation of the security responses. A first of the security responses may be activated in response to an event detected by the analysis of the video data. A first communication to a first contact may be initiated based on the analysis of the video data of the event. A second communication to a second contact may be initiated based on a response to the first communication.

An experience-aware anomaly processing system and a method for an experience-aware anomaly processing system are provided. The experience-aware anomaly processing system comprises an anomaly detection module configured to receive geographic location data with corresponding time information of a target object, and analyze target object behavior based on the geographic location data with corresponding time information of the target object; a user feedback module configured to receive user feedback from a user and model user feedback behavior when the user receives an alarm message indicating the target object is abnormal; and a decision module configured to receive user setting from the user, and make a detection decision through fusing target object behavior information corresponding to the target object behavior, user feedback behavior information corresponding to the user feedback behavior, and the user setting.

A store management system includes a first determination unit, a monitoring unit, a settlement unit, a second determination unit, and a generation unit. The first determination unit determines a customer entering a store displaying and selling a commodity. The monitoring unit monitors that the customer determined by the first determination unit carries the commodity. The settlement unit settles price of the commodity monitored by the monitoring unit as being carried by the customer, according to instruction from the customer. The second determination unit determines that the customer leaves the store. The generation unit generates history data including suspicious data indicating that the customer, identified by an identification code, is associated with an unsettled commodity being carried out of the store, when a settlement of the commodity carried by the customer which is determined by the second determination unit as leaving the store has not been completed by the settlement unit.

A method of performing movement pattern anomaly detection with targeted alerts can include receiving input from each camera of a multi-camera system and for each input: performing video content analysis; generating a critical analysis matrix associated with the input from that camera; assigning a fusion value for each vector of the critical analysis matrix using a fusion map that indicates particular fusion values associated with possible elements of the critical analysis matrix; and triggering an alert according to whether the fusion value exceeds a threshold associated with that camera. The critical analysis matrix includes output from at least two different computer vision algorithms of the video content analysis applied to the input from a camera.

An image processing method and apparatus, an electronic device and a storage medium are provided. The method includes: at least one image to be processed and at least one attribute filtering condition of an event to be monitored are obtained; event detection is performed on the at least one image to be processed to obtain an intermediate detection result of the event to be monitored; event attribute extraction is performed on the at least one image to be processed to obtain at least one attribute of the event to be monitored; and a target monitoring result of the event to be monitored is obtained according to the intermediate detection result, the at least one attribute and the at least one attribute filtering condition of the event to be monitored.

An analytical recognition system includes one or more video cameras configured to capture video and a video analytics module configured to perform real-time video processing and analyzation of the captured video and generate non-video data. The video analytic module includes one or more algorithms configured to identify an abnormal situation. Each abnormal situation alerts the video analytics module to automatically issue an alert and track one or more objects or individuals by utilizing the one or more video cameras. The abnormal situation is selected from the group consisting of action of a particular individual, non-action of a particular individual, a temporal event, and an externally generated event.