Patent Description:
<CIT> describes a process is performed at a computing device. The process computes a depth map for a scene monitored by a video camera using a plurality of IR images captured by the video camera and uses the depth map to identify a first region within the scene having historically above average false positive detected motion events. In some instances, the first region is a ceiling, a window, or a television. The process monitors a video stream provided by the video camera to identify motion events, excluding the first region, and generates a motion alert when there is detected motion in the scene outside of the first region and the detected motion satisfies threshold criteria.

<CIT> describes a method for surveillance of a predetermined volume comprising the following steps: - preparing at least one video camera designed to acquire images of a predetermined volume which is under surveillance; - defining in the images at least a first predetermined authorized region having a first level of authorization and at least a second predetermined unauthorized region, - analyzing the images to identify a moving object and to identify at least one position associated with the moving object; -comparing the position of the moving object identified with the positions of the above-mentioned authorized region and/or unauthorized region; - making available an alarm indication depending on the results of the comparison.

The present disclosure is directed towards a system, method, and computer program, embodied on a computer-readable medium, for preventing false alarms due to display images. The invention is defined in the claims. Display images may include, for example, images displayed by a television, projector, hologram, picture, poster, or the like that depict objects such as one or more human persons. The present disclosure provides for the generation of exclusionary regions where display images exist in a property. A monitoring unit can then ignore one or more portions of captured images that are determined to be associated with an exclusionary region. A monitoring system for preventing false alarms due to display images is defined in claim <NUM>.

Other aspects include corresponding methods, apparatus, and computer programs to perform actions of methods defined by instructions encoded on computer storage devices.

These and other versions may optionally include one or more of the following features. For instance, in some implementations, the exclusionary region is a portion of the property for which image data depicting an object is to be ignored by the monitoring system.

In some implementations, data identifying the exclusionary region was generated by the monitoring system based on an identification, by the monitoring system, that a portion of a different image data depicts a picture of an object on a wall, a display of a television, or a window.

In some implementations, boundaries of the exclusionary region are determined, by the monitoring system, based on a transition of first visual characteristics of portions of a wall that surround each respective side of the picture of the object on the wall, the display of the television, or the window to second visual characteristics of respective edges of the picture of the object on the wall, the display of the television, or the window.

In some implementations, the operations may further include obtaining, by the monitoring system, different image data that depicts a portion of the property, determining, by the monitoring system, that the different image data depicts a human object, based on determining, by the monitoring system, that the different image data depicts a human object, determining, by the monitoring system, whether an entirety of the depicted human object is located within an exclusionary region of the property, and based on determining, by the monitoring system, that an entirety of the depicted human object is located within an exclusionary region of the property, ignoring, by the monitoring system, the different image data, wherein ignoring the different image data includes a determination, by the monitoring system, to not trigger an event based on the different image data.

In some implementations, the operations may further include obtaining, by the monitoring system, different image data that depicts a portion of the property, and based on determining, by the monitoring system, that a human object is not depicted by the different image data, ignoring, by the monitoring system, the second image data, wherein ignoring the different image data includes a determination, by the monitoring system, to not trigger an event based on the different image data.

In some implementations, determining, by the monitoring system, that the image data depicts a human object may include obtaining, by the monitoring system, different image data that represents multiple different images that were captured before an image represented by the image data or after the image represented by the image data, and determining, by the monitoring system, whether the human object moves into the exclusionary region or whether the human object moves out of the exclusionary region based on the different image data.

In some implementations, the image data may include still image data or video image data.

In some implementations, the monitoring system may include a camera, a monitoring system control unit, or a monitoring application server.

In some implementations, the monitoring system may include a camera, monitoring system control unit, and a monitoring application server.

In some implementations, the event includes an alarm event, powering on of one or more connected lightbulbs located at the property, or recording sounds at the property using one or more microphones located at the property.

In some implementations, the portion of the property is an indoor portion of the property or an outdoor portion of the property.

A related, illustrative monitoring system for preventing false alarms due to display images can include one or more storage devices, the one or more storage devices storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include obtaining, by the monitoring system, image data that depicts a portion of a property, determining, by the monitoring system, whether the image data of the portion of the property includes an exclusionary region, based on determining, by the monitoring system, that the image data of the portion of the property includes an exclusionary region, determining, by the monitoring system, whether the image data depicts a human object within the exclusionary region, and based on determining, by the monitoring system, that the image data depicts a human object that is not located within the exclusionary region, triggering, by the monitoring system, an event based on the image data.

These and other versions may optionally include any of other features described above, one or more of the following features, or a combination thereof. For instance, in some implementations, the monitoring system can determine, that the image data depicts a human object that is located within the exclusionary region. In such implementations, the operations may also include obtaining, by the monitoring system, different image data that depicts a portion of a property, determining, by the monitoring system, whether the different image data of the portion of the property includes an exclusionary region, based on determining, by the monitoring system, that the different image data of the portion of the property includes an exclusionary region, determining, by the monitoring system, whether the different image data depicts a human object within the exclusionary region, and based on determining, by the monitoring system, that the different image data depicts a human object that is located within the exclusionary region, ignoring, by the monitoring system, the different image data, wherein ignoring the different image data includes a determination, by the monitoring system, to not trigger an event based on the different image data.

Another illustrative, related monitoring system can include one or more storage devices, the one or more storage devices storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include for example obtaining, by the monitoring system, image data that depicts a portion of a property, detecting, by the monitoring system, that the image data includes a portion of the property that should be excluded from camera surveillance, generating, by the monitoring system, data that establishes an exclusionary region for the portion of the property that should be excluded from camera surveillance, and storing, by the monitoring system, the generated data in a memory device of a component of the monitoring system.

These and other features of the present disclosure are further described below in the corresponding detail description, the claims, and the accompanying drawings.

<FIG> is a contextual diagram of a monitoring system <NUM> for preventing false alarms due to display images. The monitoring system <NUM> includes at least a monitoring system control unit <NUM>, one or more cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM> (hereinafter "130a-g"), and a network <NUM>. The network <NUM> may include a LAN, a WAN, a cellular network, a Z-wave network, a ZigBee network, a Bluetooth network, a HomePlug network, the Internet, or a combination thereof. The network <NUM> may include wired components, wireless components, or a combination thereof. For example, the network <NUM> may include a fiber optic network, an Ethernet network, a Wi-Fi network, or a combination thereof.

In some implementations, the monitoring system <NUM> may also include one or more sensors 120a, 120b, 120c, 120d, 120e, 120f, <NUM>, <NUM>, 120i, 120j (hereinafter "120a-j"), one or more drones <NUM>, one or more charging stations <NUM>, one or more connected light bulbs 166a, 166b, 166c, 166d (hereinafter "166a-d"), a user device <NUM>, a remote network <NUM>, one or more communication links <NUM>, a monitoring application server <NUM>, a central alarm station server <NUM>, or a combination thereof. The monitoring application server <NUM> can be configured to perform all of the operations described herein with respect to the monitoring system control unit <NUM>. Accordingly, the monitoring application server <NUM> can be used as a cloud-based implementation of the monitoring system control unit <NUM>. In such implementations, sensor data generated by one or more sensors 120a-j, image data generated by one or more cameras 130a-g, drone sensor data or drone image data generated by the drone <NUM>, or any other type of data generated by the monitoring system <NUM> at the property <NUM> may be communicated to the monitoring application server <NUM> for analysis via the network <NUM>, the network <NUM>, one or more communication links <NUM>, or a combination thereof. Image data may include, for example, data representing one or more features of a still image or one or more features of a video image.

The monitoring application server <NUM> may then communicate with one or more of the central alarm station server <NUM> or one or more other components of the monitoring system <NUM> at the property <NUM> using the network <NUM>, one or more communication links <NUM>, the network <NUM>, or a combination thereof regarding the results of the monitoring application server's <NUM> analysis. For example, the monitoring application server <NUM> may transmit one or more instructions that trigger an alarm at the property <NUM>, transmit a notification to the central alarm station server <NUM>, transmit notifications to the user device <NUM>, or a combination thereof - each of which may be based on based on the analysis of sensor data, image data, or the like from one or more monitoring system <NUM> components located at the property <NUM>.

The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) is configured to obtain image data generated by one or more cameras 130a-g and determine whether the image data depicts a human object. If a human object is detected in the image data, then the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) is configured to determine whether an alarm should be triggered based on the image depicting a human object. A determination of whether an alarm should be triggered based on an image depicting a human object requires the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) to determine (i) whether the human object that is depicted by one or more images actually depicts a human person that is physically present in the property <NUM> or (ii) whether the human object depicted by the one or more images merely depicts an image of a human person displayed on a television, a projection screen (or wall), a hologram, a picture, a poster or the like.

If a depicted human object is determined to be a human that is physically present in the property <NUM>, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can be configured to trigger an alarm at the property <NUM>, transmit a notification to the central station server <NUM> indicating the detection of a potential event at the property <NUM>, transmit a notification to the user device <NUM> indicating the detection of a potential event at the property <NUM>, or a combination thereof. Altematively, if a depicted human object is determined to merely be an image of a human person that is displayed on a television, a projection screen (or wall), a hologram, a picture, a poster or the like then the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can determine to not trigger an alarm, not transmit a notification to a central alarm station server, not transmit a notification to a user device <NUM>, or all of these. Because the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can analyze images to distinguish between human persons that are physically present in the property <NUM> and display images of human persons that are not physically present in the property <NUM>, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can avoid triggering false alarms based on mere images of a human person displayed on a television, a projection screen (or wall), a hologram, a picture, a poster or the like.

The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can use exclusionary regions 113a, 113b, 113c, 113d (hereinafter "113a-d") to determine (i) whether an image that depicts a human object depicts a person that is physically present in the property <NUM> or (ii) whether an image that depicts a human object merely depicts a display of a human person that is not physically present in the property <NUM>. The exclusionary regions 113a-d include portions of the property <NUM> for which image data should be ignored. Ignoring image data that is associated with an exclusionary region 113a-113d may include, for example, disregarding any image data depicting a human object that falls completely within the exclusionary region 113a-d. Accordingly, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) is configured to not trigger an alarm, not transmit a notification to the central alarm station server <NUM>, or not transmit a notification to the user device <NUM> if obtained image data depicts a human object that is completely located within an exclusionary region 113a-d.

The foregoing description generally describes the operations of the present disclosure as being performed by a monitoring system control <NUM>. The foregoing description also indicates that the operations being performed by the monitoring system control unit <NUM> may also be performed by the monitoring application server <NUM> or a camera such as one of cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>. In such altemative implementations, the monitoring application server <NUM> or one of the cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM> may perform all of the operations described with respect to the monitoring system control unit <NUM> without assistance from the monitoring system control unit <NUM>. Alternatively, in other implementations, the application server <NUM> or a camera 130a, 130b, 130c, 130d, 130e, 130f, <NUM> may work together with the monitoring system control unit <NUM> to perform the operations described here. For example, a camera <NUM> may obtain and analyze one or more images, and if the camera <NUM> determines that the one or more images depicts a human outside of one or more exclusionary regions, the camera <NUM> can broadcast data such as a notification a monitoring system control unit <NUM> (or monitoring application server <NUM>) that, when processed by the monitoring system control unit <NUM> (or monitoring application server <NUM>), causes the monitoring system control unit <NUM> to trigger an alarm event.

Though an example of an event that may be triggered, or not triggered, using the systems and methods described herein include an alarm event. The present disclosure is not so limited. Instead, other types of events may be triggered, or not triggered. Such other types of events may include powering on of one or more light bulbs at the property, recording audio sounds at the property using one or more microphones, recording and storing image data using one or more cameras at the property, or any combination thereof.

Additionally, the foregoing description, and the description below, describes features of the present disclosure as analyzing images to detect whether a human object is depicted in image data.

With reference to Room A of <FIG>, a camera <NUM> may generate image data of one or more portions of Room A during surveillance and monitoring of Room A. Surveillance and monitoring of Room A may include the camera <NUM> continuously capturing or periodically capturing image data of one or more portions of Room A. For example, in some implementations, the camera <NUM> may continuously capture image data of Room A while the monitoring system <NUM> is in an "armed" state (e.g., armed-away). In other implementations, the camera <NUM> may periodically capture images of Room A in response to the expiration of a predetermined time period, in response to motion detected by a motion sensor <NUM>, in response to a user command from the user device <NUM>, or the like. The image data may include still image data, video image data, or a combination thereof.

The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may obtain the image data generated by the camera <NUM> via one or more networks such as the networks <NUM>, <NUM>, one or more communications links <NUM>, or a combination thereof. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may analyze the obtained image data to determine whether the image data depicts one or more human objects. With reference to the example of Room A, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may determine that obtained image data depicts a human object 115a and a human object <NUM>.

The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may determine whether each of the depicted human objects 115a, <NUM> fall within an exclusionary region 113a-d. In this example, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may determine that the depicted human object 115a falls completely within an exclusionary region 113a that was generated to envelope the display of a television <NUM> having a boundary 112a. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can disregard (e.g., ignore) the human object 115a because the human object 115a falls completely within the exclusionary region 113a. Accordingly, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) will not trigger an alarm, notify the central alarm station server <NUM>, or notify a user device <NUM> based on the detection of the image depicting the human object 115a.

The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can continue to analyze the image data generated by the camera <NUM>. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) detects image data depicting the human object <NUM> and determines that the human object <NUM> is not located within an exclusionary region 113a-d. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) determines that the human object <NUM> represents a human object <NUM> that is physically present in the property <NUM> because the depicted human object <NUM> is not located within an exclusionary region 113a-d. Because the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) determines that a human object <NUM> is physically present in the property <NUM>, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can trigger an alarm, notify the central alarm station server <NUM>, notify a user device <NUM>, or a combination thereof, based on the detection of the human object <NUM> that is physically present in the property <NUM>. Accordingly, the scenario depicted in Room A results in the triggering of an alarm, transmission of a notification to the central alarm station server, transmission of a notification to a user device <NUM>, or a combination thereof, based on the detection of the human object <NUM>.

With reference to the example of Room B, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may obtain the image data generated by a camera 130e via one or more networks such as the networks <NUM>, <NUM>, one or more communications links <NUM>, or a combination thereof. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may analyze the obtained image data to determine whether the image data depicts one or more human objects. With reference to the example of Room B, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may determine that obtained image data depicts a human object 115b and a human object <NUM>.

In a similar manner to the example of Room A, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) determines that the depicted human object 115b falls completely within an exclusionary region 113b that was generated to envelope the display of a television <NUM> having a boundary 114a. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can disregard the human object 115b because the human object 115b falls completely within the exclusionary region 113b. Accordingly, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) will not trigger an alarm, notify the central alarm station server <NUM>, notify a user device <NUM>, or a combination thereof, based on a generated image depicting the human object 115b.

The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) continues to analyze the image data generated by the camera 130e. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) detects image data depicting the human object <NUM>. In this example, the image data depicts the human object <NUM> as being partially enveloped by the exclusionary region 113b and partially outside of the exclusionary region 113b. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can determine that the human object <NUM> represents a human object <NUM> that is physically present in the property <NUM> because at least a portion of the human object <NUM> is depicted outside of the exclusionary region 113b. Because the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) determines that a human person is present in the property <NUM>, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can trigger an alarm, notify the central alarm station server <NUM>, notify a user device <NUM>, or a combination thereof, based on the generated image depicting the human object <NUM>. Accordingly, the scenario depicted in Room B results in the triggering of an alarm, transmission of a notification to the central alarm station server, transmission of a notification to a user device <NUM>, or a combination thereof, based on the detection of the human object <NUM> that is determined to be physically present at the property <NUM>.

In some implementations, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may not be able to immediately determine whether the human object <NUM> is partially outside of the exclusionary region 113b. In such instances, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can analyze previously obtained image data to determine if the human object <NUM> has moved into or out of the exclusionary region. For example, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can rewind the image data, and analyze the rewound image data to determine if the human object <NUM> has entered into the exclusionary region 113b. In response to determining (i) that the human object <NUM> has entered into the exclusionary region 113b from outside the exclusionary region 113b or (ii) that the human object <NUM> has exited from the exclusionary region 113b, then the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can trigger an alarm, transmit a notification to the central alarm station server <NUM>, transmit a notification to a user device <NUM>, or a combination thereof.

With reference to Room C of <FIG>, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may obtain the image data generated by a camera 130d via one or more networks such as the networks <NUM>, <NUM>, one or more communications links <NUM>, or a combination thereof. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may analyze the obtained image data to determine whether the image data depicts one or more human objects. With reference to the example of Room C, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may determine that the obtained image data depicts a human object 115c.

The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) determines that the depicted human object 115c falls completely within an exclusionary region 113c that was generated to envelope the display of a television <NUM> having a boundary 116a. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can disregard the human object 115c because the human object 115c falls completely within the exclusionary region 113c. Accordingly, the monitoring system control unit <NUM> will not trigger an alarm, notify the central alarm station server <NUM>, or notify a user device <NUM> based on an image depicting the human object 115c in Room C.

With reference to the example of Room D the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may obtain the image data generated by a camera 130a or a camera 130b via one or more networks such as the networks <NUM>, <NUM>, one or more communications links <NUM>, or a combination thereof. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may analyze the obtained image data to determine whether the image data depicts one or more human objects. With reference to the example of Room D, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) may determine that the obtained image data depicts a human object 115d and a human object <NUM>.

In a similar manner to the example of Room A, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) determines that the depicted human object 115d falls completely within an exclusionary region 113d that was generated to envelope the display of a picture <NUM> having a boundary 118a. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can disregard the human object 115d because the human object 115d falls completely within the exclusionary region 113d. Accordingly, the monitoring system control unit <NUM> will not trigger an alarm, notify the central alarm station server <NUM>, or notify a user device <NUM> based on an image depicting the human object 115d.

As with the examples above with reference to Rooms A, B, and C, the images depicting human object 115d show the depicted human object 115d within a framed boundary 118a. The human object 115d is not ignored because the human object 115d is in the boundary 118a of the picture frame. Instead, the human object 115d is ignored because the human object 115d is fully located within the exclusionary region 113d.

In other implementations, the monitoring system control unit <NUM> (or monitoring application server <NUM> or one of cameras such as cameras 130a, 130b) may obtain images of human object 115d generated by a plurality of cameras 130a, 130b. In some implementations, the plurality of cameras 130a, 130b may be configured as stereo cameras. In such implementations, the monitoring system control unit <NUM> (or monitoring application server <NUM> or one of cameras 130a, 130b) may be configured to receive a photo of human object 115d from each of the stereo cameras 130a, 130b. The photo receiving unit (e.g., monitoring system control unit <NUM>, monitoring application server <NUM>, or one of cameras 130a, 130b) can be configured to determine the distance from a wall and a distance of the human object 115d in the images using the received images. Then, if the determined distance to the human object 115d is the same as the determined distance to the wall, the photo receiving unit can determine that human object 115d is a depiction a human object 115d on a wall as a result of a television display, projection display, photograph, poster, or the like and not a real human person standing in the property <NUM>.

The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) continues to analyze the image data generated by the camera 130a, 130b, or both. The monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) detects image data depicting the human object <NUM>. In this example, the image data depicts the human object <NUM> looking into the property <NUM> via a window <NUM>. Though human object <NUM> is looking through a framed window <NUM>, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) determines that the human object <NUM> is physically present in the property <NUM> because the human object <NUM> is not located within an exclusionary region 113a-d. For example, images of the window <NUM> that include a human object <NUM> can be analyzed by the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) to determine whether they include aspects of temporal discontinuity associated with a television display, a projection screen, hologram, or the like. In such instances, the monitoring system control unit <NUM> (or monitoring application server <NUM> or camera such as cameras 130a, 130b, 130c, 130d, 130e, 130f, <NUM>) can be configured to determine between dynamically changing lighting conditions that occur in the real, physical world from the instantaneous changing of pixel values (or other colors) in a display such as a television display. Accordingly, the scenario depicted in Room D results in the triggering of an alarm, transmission of a notification to the central alarm station server <NUM>, transmission of a notification to a user device <NUM>, or a combination thereof.

As indicated through this disclosure, any component of a monitoring system <NUM> such as a monitoring system control unit <NUM>, a monitoring application server <NUM>, or a camera <NUM> may perform analysis of image data to determine whether a human object is physically present within a property <NUM>. As an example, a camera <NUM> may capture image data of the human object <NUM>. The camera <NUM> can analyze the obtained image data and determine whether the image data includes a human. Once the camera <NUM> determines that the image data includes a human object <NUM>, then the camera <NUM> can determine whether the image data depicts the human object <NUM> in an exclusionary region. In the example of Room A, the camera <NUM> can determine that the human object <NUM> is not within an exclusionary region. In such instances, the camera can transmit data such as a notification to a monitoring system control unit <NUM> or monitoring application server <NUM> that, when processed by the monitoring system control unit <NUM> or the monitoring application server <NUM>, causes the monitoring system control unit <NUM> or monitoring application server <NUM> to trigger an alarm event.

Alternatively, assume that the camera <NUM> can capture image data that only depicts the human object 115a and not any other human object. In such implementations, the camera <NUM> can determine whether the human object 115a resides within an exclusionary region. In this example, the camera <NUM> can determine that the human object 115a falls completely within the exclusionary region 113a and disregard (e.g., ignore) the image data. Disregarding (e.g., ignoring) the image data may include, for example, determining, by the camera <NUM> to not transmit data to the monitoring application server <NUM> or monitoring system control unit <NUM> that causes the monitoring application server <NUM> or monitoring system control unit <NUM> to trigger an alarm event.

<FIG> is a contextual diagram of monitoring system <NUM> for detecting and generating an exclusionary region. The monitoring system <NUM> for detecting an exclusionary region may include, for example, a monitoring system control unit <NUM> (or a monitoring application server <NUM>), a camera 130e, and a network <NUM>.

A component of the monitoring <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may begin the process of detecting an exclusionary region 113a by obtaining image data depicting portions of Room A from one or more cameras such as the camera 130e. The monitoring system component can analyze the obtained image data in order to determine if there are any portions of Room A that should be excluded from video surveillance. Determining if there are any portions of Room A that should be excluded from video surveillance may include, for example, scanning for displays (e.g., televisions), holograms, projections, framed pictures, posters, or any other displayed image that has the potential to create a representation of a human object that is not physically present in the property <NUM>.

A component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e can analyze image data to detect displays (e.g., televisions), holograms, projections, framed pictures, posters, or the like. In some implementations, detecting displays (e.g., televisions), holograms, projections, framed pictures, posters, or the like may include identifying transitions between a first surface of a wall (or other surface) and a second surface of a display (e.g., television), framed picture, poster, or the like. For example, with reference to the television <NUM> of <FIG>, a monitoring system <NUM> component can detect each respective boundary 212a, 212b, 212c, 212d of the television <NUM> by detecting a difference in the color, contrast, texture, static look, or the like in the area surrounding boundaries 212a, 212b, 212c, 212d versus the color, contrast, texture, and dynamically changing look of the display within the respective boundaries 212a, 212b, 212c, 212d. For example, the monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e can determine between dynamically changing lighting conditions that occur on a surface such as a wall in a real, physical world from the instantaneous changing of pixel values (or other colors) in a display such as a television display.

In the same, or other implementations, a monitoring system <NUM> component such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may be configured to detect displays (e.g., televisions), holograms, projection screens, or the like using different techniques that are specifically geared towards identifying such display objects. For example, the monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may use a machine learning model trained on the appearance of screens, or the frames and items typically surrounding them (such as a laptop). In such instances, the machine leaming model may be trained using labeled training data that includes an image and a label that indicates whether the images is a real, physical world image or a display object displayed by a display (e.g., television), hologram, projection screen, or the like. Such training data may include, for example, video image data representing a television display displaying a human using lighting in a manner that depicts unique characteristics of a television display and labeled as (i) display image, (ii) not a real, physical world image, or (iii) the like. Similarly, other training data items may include, for example, video image data that depicts a real human physically standing in front of a wall and labeled as (i) not a display image, (ii) a real, physical world image, or (iii) the like. Such training data items can be used to train a machine learning model such as a deep neural network to distinguish between television displays outputting video or images of a human and a real, physical world human standing in a property. Other types of training data items may also be used to train the machine learning model such as training data items showing a picture hanging on a wall and labeled as non-real world image.

In yet other implementations, a monitoring system <NUM> component such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may be configured to detect displays (e.g., televisions), holograms, projection screens, or the like using different techniques. For example, the monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e can perform a shape-based analysis to determine whether a captured image includes a real world object or a display object provided for output by a display (e.g., television), hologram, projection screen, or the like. By way of example, performance of a shape-based analysis can enable a component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e to analyze image data to distinguish between a <NUM>-dimensional display of a human on a television screen and a <NUM>-dimensional shape of a real, physical world human.

In some implementations, a component of the monitoring system <NUM> monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e can use a combination of multiple different analyses such as light-based analysis and shaped-based analysis. For example, a component of monitoring system <NUM> monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e can perform a shape-based analysis on a hologram of a human and a real, physical world human and determine that both the hologram of the human and the real, physical world human are each <NUM>-dimensional. However, the component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e can perform additional analyses such as a light-based analysis and determine that a difference in light characteristics such as flickering of lighting used to generate the hologram is different than the light that reflects off of a real, physical world human.

In yet other implementations, a component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may be configured to detect displays (e.g., televisions), holograms, projection screens, or the like using different techniques. For example, a component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may observe images captured of a portion of a property over a period of time. Based on this analysis, the component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may determine that images of a portion of the property are, from time-to-time, associated with a rectangle (or other shape of a display) that is relatively black. The component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may also determine that there are instances where the images of the portion of the property change from black to providing, for output, display objects. The component of the monitoring system <NUM> such as the monitoring system control unit <NUM>, the monitoring application server <NUM>, or the camera 130e may determine, based on the change of the display from off-to-on, that the portion of the property is associated with a display (e.g., a television), hologram, projection screen, or the like.

In yet other implementations, a component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may be configured to detect displays (e.g., televisions), holograms, projection screens, or the like using different techniques. For example, the component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may observe their dynamic range in relationship to the rest of the scene. This may include identifying object movement and determining whether the objects move beyond the ranges established by the boundaries 212a, 212b, 212c, 212d of a potential display.

The component of the monitoring system <NUM> such as monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e may generate an exclusionary region 113a that extends to at least the respective boundaries 212a, 212b, 212c, 212d of the television <NUM>. The exclusionary region 113a can establish a region of the Room A that will not be monitored for the presence of human objects that fall completely within the exclusionary region 113a using the image data generated by the camera 130e. Instead, any human object detected as falling completely within the exclusionary region 113a will be ignored. Data defining the location and scope of the exclusionary region 113a is generated by the component of the monitoring system <NUM> and stored by the component of the monitoring system <NUM> such as the monitoring system control unit <NUM>, monitoring application server <NUM>, or camera 130e.

Though aspects of the present disclosure are directed towards use of a component of the monitoring system <NUM> to analyze image data and determine, based on component's analysis of the image data, whether one or more locations of a property are to be designated as an exclusionary region. The present disclosure need not be so limited. For example, instead of the component of the monitoring system <NUM> analyzing image data, detecting an exclusionary region, generated data defining the location and scope of the exclusionary region, and storing the generated data defining the location and scope of the exclusionary region - other methods may be used. Such other methods may include, for example, a user inputting data defining a location and scope of an exclusionary region to the component of the monitoring system <NUM> for storage in a storage device of the component of the monitoring system <NUM>.

The systems of <FIG> and <FIG> are described with reference to indoor portions of a property. However, the present disclosure need not be so limited. Instead, the systems described with reference to <FIG> and <FIG>, as well as their features of their corresponding processes described above and below, can also work for outdoor portions of the property, as well.

<FIG> is flowchart of example of a process <NUM> for detecting an exclusionary region. Generally, the process <NUM> may include, for example, obtaining, by a monitoring system, image data that depicts a portion of a property (<NUM>), detecting, by the monitoring system, that the image data includes a portion of the property that should be excluded from camera surveillance (<NUM>), generating, by the monitoring system, data that establishes an exclusionary region for the portion of the property that should be excluded from camera surveillance (<NUM>), and storing, by the monitoring system, the generated data in a memory device of the component of the monitoring system (<NUM>).

In some implementations, the process <NUM> for detecting an exclusionary region may be performed by a backend server component of the monitoring system such as a monitoring application server, or other server computer. In other implementations, a different component of the monitoring system such as a camera can perform the processes of detecting an exclusionary region.

<FIG> is a flowchart of an example of a process <NUM> for preventing false alarms due to display images. Generally, the process <NUM> includes obtaining, by a monitoring system, image data that depicts a portion of a property (<NUM>), determining, by the monitoring system, whether a human is depicted by the image (<NUM>), determining, by the monitoring system, whether the depicted human resides within an exclusionary region of the property (<NUM>), and based on determining, by the monitoring system, that the depicted human does not reside within an exclusionary region of the property, triggering an alarm event (<NUM>).

The features of process <NUM> are presented in a first particular order beginning with stage <NUM> and ending with stage <NUM>. However, the present disclosure need not be so limited. For example, in some implementations, the stages of process <NUM> can be executed in a different order. By way of example, in some implementations, a system can perform a variation of stage <NUM> before stage <NUM>. That is, the system can determine whether obtained image data include an exclusionary region, and if the obtained image data includes an exclusionary region, the system can determine whether a human object exists within the exclusionary region.

<FIG> is a block diagram of a system <NUM> that includes components that can be used to implement the systems of <FIG> or <FIG>.

The electronic system <NUM> includes a network <NUM>, a monitoring system control unit <NUM>, one or more user devices <NUM>, <NUM>, a monitoring application server <NUM>, and a central alarm station server <NUM>. In some examples, the network <NUM> facilitates communications between the monitoring system control unit <NUM>, the one or more user devices <NUM>, <NUM>, the monitoring application server <NUM>, and the central alarm station server <NUM>.

The network <NUM> is configured to enable exchange of electronic communications between devices connected to the network <NUM>. For example, the network <NUM> may be configured to enable exchange of electronic communications between the monitoring system control unit <NUM>, the one or more user devices <NUM>, <NUM>, the monitoring application server <NUM>, and the central alarm station server <NUM>. The network <NUM> may include, for example, one or more of the Internet, Wide Area Networks (WANs), Local Area Networks (LANs), analog or digital wired and wireless telephone networks (e.g., a public switched telephone network (PSTN), Integrated Services Digital Network (ISDN), a cellular network, and Digital Subscriber Line (DSL)), radio, television, cable, satellite, or any other delivery or tunneling mechanism for carrying data. Network <NUM> may include multiple networks or subnetworks, each of which may include, for example, a wired or wireless data pathway. The network <NUM> may include a circuit-switched network, a packet-switched data network, or any other network able to carry electronic communications (e.g., data or voice communications). For example, the network <NUM> may include networks based on the Intemet protocol (IP), asynchronous transfer mode (ATM), the PSTN, packet-switched networks based on IP, X. <NUM>, or Frame Relay, or other comparable technologies and may support voice using, for example, VoIP, or other comparable protocols used for voice communications. The network <NUM> may include one or more networks that include wireless data channels and wireless voice channels. The network <NUM> may be a wireless network, a broadband network, or a combination of networks including a wireless network and a broadband network.

The monitoring system control unit <NUM> includes a controller <NUM>, a network module <NUM>, and storage unit <NUM>. The controller <NUM> is configured to control a monitoring system (e.g., a home alarm or security system) that includes the monitoring system control unit <NUM>. In some examples, the controller <NUM> may include a processor or other control circuitry configured to execute instructions of a program that controls operation of an alarm system. In these examples, the controller <NUM> may be configured to receive input from sensors, detectors, or other devices included in the alarm system and control operations of devices included in the alarm system or other household devices (e.g., a thermostat, an appliance, lights, etc.). For example, the controller <NUM> may be configured to control operation of the network module <NUM> included in the monitoring system control unit <NUM>.

The monitoring system control unit <NUM> is configured to obtain image data generated by one or more cameras 530and determine whether the image data depicts a human object. If a human object is detected in the image data, then the monitoring system control unit <NUM> is configured to determine whether an alarm should be triggered based on the image depicting a human object. A determination of whether an alarm should be triggered based on an image depicting a human object requires the monitoring system control unit <NUM> to determine (i) whether the human object that is depicted by one or more images actually depicts a human that is physically present in the property or (ii) whether the human object depicted by the one or more images merely depicts an image of a human displayed on a television, a projection screen (or wall), a hologram, a picture, a poster or the like.

If a depicted human object is determined, by the monitoring system control unit <NUM>, to be a human that is physically present in the property, the monitoring system control unit <NUM> can be configured to trigger an alarm at the property, transmit a notification to the central alarm station server <NUM> indicating the detection of a potential event at the property, transmit a notification to the user device <NUM>, <NUM> indicating the detection of a potential event at the property, or a combination thereof. Altematively, if a depicted human object is determined to merely be an image of a human that is displayed on a television, a projection screen (or wall), a hologram, a picture, a poster or the like then the monitoring system control unit <NUM> can determine to not trigger an alarm, not transmit a notification to a central alarm station server <NUM>, not transmit a notification to a user device <NUM>, <NUM>, or all of these. Because the monitoring system control unit <NUM> can analyze images to distinguish between human(s) that is/are physically present in the property and display images of human(s) that is/are not physically present in the property, the monitoring system control unit <NUM> can avoid triggering false alarms based on mere images of a human displayed on a television, a projection screen (or wall), a hologram, a picture, a poster or the like.

The monitoring system control unit <NUM> can generate and use exclusionary regions to determine (i) whether an image that depicts a human object depicts a human that is physically present in the property or (ii) whether an image that depicts a human object merely depicts a display of a human that is not physically present in the property. The exclusionary regions include portions of the property for which image data should be ignored. The monitoring system control unit <NUM> can ignore image data that is associated with an exclusionary region by, for example, disregarding any image data depicting a human object that falls completely within the exclusionary region. Accordingly, the monitoring system control unit <NUM> is configured to not trigger an alarm, not transmit a notification to the central alarm station server <NUM>, or not transmit a notification to the user device <NUM>, 550if obtained image data depicts a human object that is completely located within an exclusionary region.

In some implementations, the monitoring system control unit <NUM> may store received input from sensors, detectors, user devices <NUM> and <NUM>, or other devices included in system <NUM> may be stored in the storage unit <NUM>. The monitoring system control unit <NUM> may analyze the stored input or use the network module <NUM> to transmit the stored input to the monitoring application server for analysis. The stored input may be analyzed by the monitoring system control unit <NUM> to determine whether an exclusionary region needs to be created based on the stored input. Alternatively, or in addition, the stored input may be analyzed to determine whether a human object depicted in an exclusionary region should trigger the sounding of an alarm, trigger a notification of an event to be sent to the central alarm station server <NUM>, trigger a notification of an event to be sent to a user device <NUM>, <NUM>, or the like.

The network module <NUM> is a communication device configured to exchange communications over the network <NUM>. The network module <NUM> may be a wireless communication module configured to exchange wireless communications over the network <NUM>. For example, the network module <NUM> may be a wireless communication device configured to exchange communications over a wireless data channel and a wireless voice channel. In this example, the network module <NUM> may transmit alarm data over a wireless data channel and establish a two-way voice communication session over a wireless voice channel. The wireless communication device may include one or more of a LTE module, a GSM module, a radio modem, cellular transmission module, or any type of module configured to exchange communications in one of the following formats: LTE, GSM or GPRS, CDMA, EDGE or EGPRS, EV-DO or EVDO, UMTS, or IP.

The network module <NUM> also may be a wired communication module configured to exchange communications over the network <NUM> using a wired connection. For instance, the network module <NUM> may be a modem, a network interface card, or another type of network interface device. The network module <NUM> may be an Ethernet network card configured to enable the monitoring system control unit <NUM> to communicate over a local area network and/or the Internet. The network module <NUM> also may be a voiceband modem configured to enable the alarm panel to communicate over the telephone lines of Plain Old Telephone Systems (POTS).

The monitoring system that includes the monitoring system control unit <NUM> includes one or more sensors or detectors. For example, the monitoring system may include multiple sensors <NUM>. The sensors <NUM> may include a contact sensor, a motion sensor, a glass break sensor, or any other type of sensor included in an alarm system or security system. The sensors <NUM> also may include an environmental sensor, such as a temperature sensor, a water sensor, a rain sensor, a wind sensor, a light sensor, a smoke detector, a carbon monoxide detector, an air quality sensor, etc. The sensors <NUM> further may include a health monitoring sensor, such as a prescription bottle sensor that monitors taking of prescriptions, a blood pressure sensor, a blood sugar sensor, a bed mat configured to sense presence of liquid (e.g., bodily fluids) on the bed mat, etc. In some examples, the sensors <NUM> may include a radiofrequency identification (RFID) sensor that identifies a particular article that includes a preassigned RFID tag.

The monitoring system control unit <NUM> communicates with the automation module <NUM> and the camera <NUM> to perform surveillance or monitoring. The automation module <NUM> is connected to one or more devices that enable home automation control. For instance, the automation module <NUM> may be connected to one or more lighting systems and may be configured to control operation of the one or more lighting systems. Also, the automation module <NUM> may be connected to one or more electronic locks at the property and may be configured to control operation of the one or more electronic locks (e.g., control Z-Wave locks using wireless communications in the Z-Wave protocol. Further, the automation module <NUM> may be connected to one or more appliances at the property and may be configured to control operation of the one or more appliances. The automation module <NUM> may include multiple modules that are each specific to the type of device being controlled in an automated manner. The automation module <NUM> may control the one or more devices based on commands received from the monitoring system control unit <NUM>. For instance, the automation module <NUM> may cause a lighting system to illuminate an area to provide a better image of the area when captured by a camera <NUM>.

The camera <NUM> may be a video/photographic camera or other type of optical sensing device configured to capture images. For instance, the camera <NUM> may be configured to capture images of an area within a building monitored by the monitoring system control unit <NUM>. The camera <NUM> may be configured to capture single, static images of the area and also video images of the area in which multiple images of the area are captured at a relatively high frequency (e.g., thirty images per second). The camera <NUM> may be controlled based on commands received from the monitoring system control unit <NUM>.

The camera <NUM> may be triggered by several different types of techniques. For instance, a Passive Infra Red (PIR) motion sensor may be built into the camera <NUM> and used to trigger the camera <NUM> to capture one or more images when motion is detected. The camera <NUM> also may include a microwave motion sensor built into the camera and used to trigger the camera <NUM> to capture one or more images when motion is detected. The camera <NUM> may have a "normally open" or "normally closed" digital input that can trigger capture of one or more images when external sensors (e.g., the sensors <NUM>, PIR, door/window, etc.) detect motion or other events. In some implementations, the camera <NUM> receives a command to capture an image when external devices detect motion or another potential alarm event. The camera <NUM> may receive the command from the controller <NUM> or directly from one of the sensors <NUM>.

In some examples, the camera <NUM> triggers integrated or external illuminators (e.g., Infra Red, Z-wave controlled "white" lights, lights controlled by the module <NUM>, etc.) to improve image quality when the scene is dark. An integrated or separate light sensor may be used to determine if illumination is desired and may result in increased image quality.

The camera <NUM> may be programmed with any combination of time/day schedules, system "arming state", or other variables to determine whether images should be captured or not when triggers occur. The camera <NUM> may enter a low-power mode when not capturing images. In this case, the camera <NUM> may wake periodically to check for inbound messages from the controller <NUM>. The camera <NUM> may be powered by intemal, replaceable batteries if located remotely from the monitoring control unit <NUM>. The camera <NUM> may employ a small solar cell to recharge the battery when light is available. Altematively, the camera <NUM> may be powered by the controller's <NUM> power supply if the camera <NUM> is co-located with the controller <NUM>.

In some implementations, the camera <NUM> communicates directly with the monitoring application server <NUM> over the Internet. In these implementations, image data captured by the camera <NUM> does not pass through the monitoring system control unit <NUM> and the camera <NUM> receives commands related to operation from the monitoring application server <NUM>.

The system <NUM> further includes one or more robotic devices <NUM> and <NUM>. The robotic devices <NUM> and <NUM> may be any type of robots that are capable of moving and taking actions that assist monitoring user behavior patterns. For example, the robotic devices <NUM> and <NUM> may include drones that are capable of moving throughout a property based on automated control technology and/or user input control provided by a user. In this example, the drones may be able to fly, roll, walk, or otherwise move about the property. The drones may include helicopter type devices (e.g., quad copters), rolling helicopter type devices (e.g., roller copter devices that can fly and also roll along the ground, walls, or ceiling) and land vehicle type devices (e.g., automated cars that drive around a property). In some cases, the robotic devices <NUM> and <NUM> may be robotic devices that are intended for other purposes and merely associated with the monitoring system <NUM> for use in appropriate circumstances. For instance, a robotic vacuum cleaner device may be associated with the monitoring system <NUM> as one of the robotic devices <NUM> and <NUM> and may be controlled to take action responsive to monitoring system events.

In some examples, the robotic devices <NUM> and <NUM> automatically navigate within a property. In these examples, the robotic devices <NUM> and <NUM> include sensors and control processors that guide movement of the robotic devices <NUM> and <NUM> within the property. For instance, the robotic devices <NUM> and <NUM> may navigate within the property using one or more cameras, one or more proximity sensors, one or more gyroscopes, one or more accelerometers, one or more magnetometers, a global positioning system (GPS) unit, an altimeter, one or more sonar or laser sensors, and/or any other types of sensors that aid in navigation about a space. The robotic devices <NUM> and <NUM> may include control processors that process output from the various sensors and control the robotic devices <NUM> and <NUM> to move along a path that reaches the desired destination and avoids obstacles. In this regard, the control processors detect walls or other obstacles in the property and guide movement of the robotic devices <NUM> and <NUM> in a manner that avoids the walls and other obstacles.

In addition, the robotic devices <NUM> and <NUM> may store data that describes attributes of the property. For instance, the robotic devices <NUM> and <NUM> may store a floorplan and/or a three-dimensional model of the property that enables the robotic devices <NUM> and <NUM> to navigate the property. During initial configuration, the robotic devices <NUM> and <NUM> may receive the data describing attributes of the property, determine a frame of reference to the data (e.g., a home or reference location in the property), and navigate the property based on the frame of reference and the data describing attributes of the property. Further, initial configuration of the robotic devices <NUM> and <NUM> also may include learning of one or more navigation patterns in which a user provides input to control the robotic devices <NUM> and <NUM> to perform a specific navigation action (e.g., fly to an upstairs bedroom and spin around while capturing video and then return to a home charging base). In this regard, the robotic devices <NUM> and <NUM> may leam and store the navigation patterns such that the robotic devices <NUM> and <NUM> may automatically repeat the specific navigation actions upon a later request.

In addition to navigation patterns that are leamed during initial configuration, the robotic devices <NUM> and <NUM> may also be configured to leam additional navigational patterns. For instance, a robotic device <NUM> and <NUM> can be programmed to travel along particular navigational paths in response to an instruction from the monitoring system control unit <NUM> to investigate a portion of the property associated with a sensor that broadcasted data that, when processed by the monitoring system control unit <NUM>, indicates the existence of an event.

In some examples, the robotic devices <NUM> and <NUM> may include data capture and recording devices. In these examples, the robotic devices <NUM> and <NUM> may include one or more cameras, one or more motion sensors, one or more microphones, one or more biometric data collection tools, one or more temperature sensors, one or more humidity sensors, one or more air flow sensors, and/or any other types of sensors that may be useful in capturing monitoring data related to the property and users in the property. The one or more biometric data collection tools may be configured to collect biometric samples of a person in the home with or without contact of the person. For instance, the biometric data collection tools may include a fingerprint scanner, a hair sample collection tool, a skin cell collection tool, and/or any other tool that allows the robotic devices <NUM> and <NUM> to take and store a biometric sample that can be used to identify the person (e.g., a biometric sample with DNA that can be used for DNA testing).

In some implementations, the robotic devices <NUM> and <NUM> may include output devices. In these implementations, the robotic devices <NUM> and <NUM> may include one or more displays, one or more speakers, one or more projectors, and/or any type of output devices that allow the robotic devices <NUM> and <NUM> to communicate information to a nearby user. The one or more projectors may include projectors that project a two-dimensional image onto a surface (e.g., wall, floor, or ceiling) and/or holographic projectors that project three-dimensional holograms into a nearby space.

The robotic devices <NUM> and <NUM> also may include a communication module that enables the robotic devices <NUM> and <NUM> to communicate with the monitoring system control unit <NUM>, each other, and/or other devices. The communication module may be a wireless communication module that allows the robotic devices <NUM> and <NUM> to communicate wirelessly. For instance, the communication module may be a Wi-Fi module that enables the robotic devices <NUM> and <NUM> to communicate over a local wireless network at the property. The communication module further may be a <NUM> wireless communication module that enables the robotic devices <NUM> and <NUM> to communicate directly with the monitoring system control unit <NUM>. Other types of short-range wireless communication protocols, such as Bluetooth, Bluetooth LE, Z-wave, ZigBee, etc., may be used to allow the robotic devices <NUM> and <NUM> to communicate with other devices in the property.

The robotic devices <NUM> and <NUM> further may include processor and storage capabilities. The robotic devices <NUM> and <NUM> may include any suitable processing devices that enable the robotic devices <NUM> and <NUM> to operate applications and perform the actions described throughout this disclosure. In addition, the robotic devices <NUM> and <NUM> may include solid state electronic storage that enables the robotic devices <NUM> and <NUM> to store applications, configuration data, collected sensor data, and/or any other type of information available to the robotic devices <NUM> and <NUM>.

The robotic devices <NUM> and <NUM> are associated with one or more charging stations <NUM> and <NUM>. The charging stations <NUM> and <NUM> may be located at predefined home base or reference locations in the property. The robotic devices <NUM> and <NUM> may be configured to navigate to the charging stations <NUM> and <NUM> after completion of tasks needed to be performed for the monitoring system <NUM>. For instance, after completion of a monitoring operation or upon instruction by the monitoring system control unit <NUM>, the robotic devices <NUM> and <NUM> may be configured to automatically fly to and land on one of the charging stations <NUM> and <NUM>. In this regard, the robotic devices <NUM> and <NUM> may automatically maintain a fully charged battery in a state in which the robotic devices <NUM> and <NUM> are ready for use by the monitoring system <NUM>.

The charging stations <NUM> and <NUM> may be contact based charging stations and/or wireless charging stations. For contact based charging stations, the robotic devices <NUM> and <NUM> may have readily accessible points of contact that the robotic devices <NUM> and <NUM> are capable of positioning and mating with a corresponding contact on the charging station. For instance, a helicopter type robotic device may have an electronic contact on a portion of its landing gear that rests on and mates with an electronic pad of a charging station when the helicopter type robotic device lands on the charging station. The electronic contact on the robotic device may include a cover that opens to expose the electronic contact when the robotic device is charging and closes to cover and insulate the electronic contact when the robotic device is in operation.

For wireless charging stations, the robotic devices <NUM> and <NUM> may charge through a wireless exchange of power. In these cases, the robotic devices <NUM> and <NUM> need only locate themselves closely enough to the wireless charging stations for the wireless exchange of power to occur. In this regard, the positioning needed to land at a predefined home base or reference location in the property may be less precise than with a contact based charging station. Based on the robotic devices <NUM> and <NUM> landing at a wireless charging station, the wireless charging station outputs a wireless signal that the robotic devices <NUM> and <NUM> receive and convert to a power signal that charges a battery maintained on the robotic devices <NUM> and <NUM>.

The sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> communicate with the controller <NUM> over communication links <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>. The communication links <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> may be a wired or wireless data pathway configured to transmit signals from the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> to the controller <NUM>. The sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> may continuously transmit sensed values to the controller <NUM>, periodically transmit sensed values to the controller <NUM>, or transmit sensed values to the controller <NUM> in response to a change in a sensed value.

The communication links <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> may include a local network. The sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> and the controller <NUM> may exchange data and commands over the local network. The local network may include <NUM> "Wi-Fi" wireless Ethernet (e.g., using low-power Wi-Fi chipsets), Z-Wave, ZigBee, Bluetooth, "Homeplug" or other "Powerline" networks that operate over AC wiring, and a Category <NUM> (CAT5) or Category <NUM> (CAT6) wired Ethernet network. The local network may be a mesh network constructed based on the devices connected to the mesh network.

The monitoring application server <NUM> is an electronic device configured to provide monitoring services by exchanging electronic communications with the monitoring system control unit <NUM>, the one or more user devices <NUM>, <NUM>, and the central alarm station server <NUM> over the network <NUM>. For example, the monitoring application server <NUM> may be configured to monitor events (e.g., alarm events) generated by the monitoring system control unit <NUM>. In this example, the monitoring application server <NUM> may exchange electronic communications with the network module <NUM> included in the monitoring system control unit <NUM> to receive information regarding events (e.g., alarm events) detected by the monitoring system control unit <NUM>. The monitoring application server <NUM> also may receive information regarding events (e.g., alarm events) from the one or more user devices <NUM>, <NUM>.

In some examples, the monitoring application server <NUM> may route alarm data received from the network module <NUM> or the one or more user devices <NUM>, <NUM> to the central alarm station server <NUM>. For example, the monitoring application server <NUM> may transmit the alarm data to the central alarm station server <NUM> over the network <NUM>.

The monitoring application server <NUM> may store sensor and image data received from the monitoring system and perform analysis of sensor and image data received from the monitoring system. Based on the analysis, the monitoring application server <NUM> may communicate with and control aspects of the monitoring system control unit <NUM> or the one or more user devices <NUM>, <NUM>.

The central alarm station server <NUM> is an electronic device configured to provide alarm monitoring service by exchanging communications with the monitoring system control unit <NUM>, the one or more mobile devices <NUM>, <NUM>, and the monitoring application server <NUM> over the network <NUM>. For example, the central alarm station server <NUM> may be configured to monitor alarm events generated by the monitoring system control unit <NUM>. In this example, the central alarm station server <NUM> may exchange communications with the network module <NUM> included in the monitoring system control unit <NUM> to receive information regarding alarm events detected by the monitoring system control unit <NUM>. The central alarm station server <NUM> also may receive information regarding alarm events from the one or more mobile devices <NUM>, <NUM> and/or the monitoring application server <NUM>.

The central alarm station server <NUM> is connected to multiple terminals <NUM> and <NUM>. The terminals <NUM> and <NUM> may be used by operators to process alarm events. For example, the central alarm station server <NUM> may route alarm data to the terminals <NUM> and <NUM> to enable an operator to process the alarm data. The terminals <NUM> and <NUM> may include general-purpose computers (e.g., desktop personal computers, workstations, or laptop computers) that are configured to receive alarm data from a server in the central alarm station server <NUM> and render a display of information based on the alarm data. For instance, the controller <NUM> may control the network module <NUM> to transmit, to the central alarm station server <NUM>, alarm data indicating that a sensor <NUM> detected a door opening when the monitoring system was armed. The central alarm station server <NUM> may receive the alarm data and route the alarm data to the terminal <NUM> for processing by an operator associated with the terminal <NUM>. The terminal <NUM> may render a display to the operator that includes information associated with the alarm event (e.g., the name of the user of the alarm system, the address of the building the alarm system is monitoring, the type of alarm event, etc.) and the operator may handle the alarm event based on the displayed information.

In some implementations, the terminals <NUM> and <NUM> may be mobile devices or devices designed for a specific function. Although <FIG> illustrates two terminals for brevity, actual implementations may include more (and, perhaps, many more) terminals.

The one or more user devices <NUM>, <NUM> are devices that host and display user interfaces. For instance, the user device <NUM> is a mobile device that hosts one or more native applications (e.g., the native surveillance application <NUM>). The user device <NUM> may be a cellular phone or a non-cellular locally networked device with a display. The user device <NUM> may include a cell phone, a smart phone, a tablet PC, a personal digital assistant ("PDA"), or any other portable device configured to communicate over a network and display information. For example, implementations may also include Blackberry-type devices (e.g., as provided by Research in Motion), electronic organizers, iPhone-type devices (e.g., as provided by Apple), iPod devices (e.g., as provided by Apple) or other portable music players, other communication devices, and handheld or portable electronic devices for gaming, communications, and/or data organization. The user device <NUM> may perform functions unrelated to the monitoring system, such as placing personal telephone calls, playing music, playing video, displaying pictures, browsing the Internet, maintaining an electronic calendar, etc..

The user device <NUM> includes a native surveillance application <NUM>. The native surveillance application <NUM> refers to a software/firmware program running on the corresponding mobile device that enables the user interface and features described throughout. The user device <NUM> may load or install the native surveillance application <NUM> based on data received over a network or data received from local media. The native surveillance application <NUM> runs on mobile devices platforms, such as iPhone, iPod touch, Blackberry, Google Android, Windows Mobile, etc. The native surveillance application <NUM> enables the user device <NUM> to receive and process image and sensor data from the monitoring system.

The user device <NUM> may be a general-purpose computer (e.g., a desktop personal computer, a workstation, or a laptop computer) that is configured to communicate with the monitoring application server <NUM> and/or the monitoring system control unit <NUM> over the network <NUM>. The user device <NUM> may be configured to display a surveillance monitoring user interface <NUM> that is generated by the user device <NUM> or generated by the monitoring application server <NUM>. For example, the user device <NUM> may be configured to display a user interface (e.g., a web page) provided by the monitoring application server <NUM> that enables a user to perceive images captured by the camera <NUM> and/or reports related to the monitoring system. Although <FIG> illustrates two user devices for brevity, actual implementations may include more (and, perhaps, many more) or fewer user devices.

In some implementations, the one or more user devices <NUM>, <NUM> communicate with and receive monitoring system data from the monitoring system control unit <NUM> using the communication link <NUM>. For instance, the one or more user devices <NUM>, <NUM> may communicate with the monitoring system control unit <NUM> using various local wireless protocols such as Wi-Fi, Bluetooth, Z-wave, ZigBee, HomePlug (Ethernet over powerline), or wired protocols such as Ethernet and USB, to connect the one or more user devices <NUM>, <NUM> to local security and automation equipment. The one or more user devices <NUM>, <NUM> may connect locally to the monitoring system and its sensors and other devices. The local connection may improve the speed of status and control communications because communicating through the network <NUM> with a remote server (e.g., the monitoring application server <NUM>) may be significantly slower.

Although the one or more user devices <NUM>, <NUM> are shown as communicating with the monitoring system control unit <NUM>, the one or more user devices <NUM>, <NUM> may communicate directly with the sensors and other devices controlled by the monitoring system control unit <NUM>. In some implementations, the one or more user devices <NUM>, <NUM> replace the monitoring system control unit <NUM> and perform the functions of the monitoring system control unit <NUM> for local monitoring and long range/offsite communication.

In other implementations, the one or more user devices <NUM>, <NUM> receive monitoring system data captured by the monitoring system control unit <NUM> through the network <NUM>. The one or more user devices <NUM>, <NUM> may receive the data from the monitoring system control unit <NUM> through the network <NUM> or the monitoring application server <NUM> may relay data received from the monitoring system control unit <NUM> to the one or more user devices <NUM>, <NUM> through the network <NUM>. In this regard, the monitoring application server <NUM> may facilitate communication between the one or more user devices <NUM>, <NUM> and the monitoring system.

In some implementations, the one or more user devices <NUM>, <NUM> may be configured to switch whether the one or more user devices <NUM>, <NUM> communicate with the monitoring system control unit <NUM> directly (e.g., through link <NUM>) or through the monitoring application server <NUM> (e.g., through network <NUM>) based on a location of the one or more user devices <NUM>, <NUM>. For instance, when the one or more user devices <NUM>, <NUM> are located close to the monitoring system control unit <NUM> and in range to communicate directly with the monitoring system control unit <NUM>, the one or more user devices <NUM>, <NUM> use direct communication. When the one or more user devices <NUM>, <NUM> are located far from the monitoring system control unit <NUM> and not in range to communicate directly with the monitoring system control unit <NUM>, the one or more user devices <NUM>, <NUM> use communication through the monitoring application server <NUM>.

Although the one or more user devices <NUM>, <NUM> are shown as being connected to the network <NUM>, in some implementations, the one or more user devices <NUM>, <NUM> are not connected to the network <NUM>. In these implementations, the one or more user devices <NUM>, <NUM> communicate directly with one or more of the monitoring system components and no network (e.g., Internet) connection or reliance on remote servers is needed.

In some implementations, the one or more user devices <NUM>, <NUM> are used in conjunction with only local sensors and/or local devices in a house. In these implementations, the system <NUM> only includes the one or more user devices <NUM>, <NUM>, the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM>. The one or more user devices <NUM>, <NUM> receive data directly from the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> and sends data directly to the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM>. The one or more user devices <NUM>, <NUM> provide the appropriate interfaces/processing to provide visual surveillance and reporting.

In other implementations, the system <NUM> further includes network <NUM> and the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> are configured to communicate sensor and image data to the one or more user devices <NUM>, <NUM> over network <NUM> (e.g., the Internet, cellular network, etc.). In yet another implementation, the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> (or a component, such as a bridge/router) are intelligent enough to change the communication pathway from a direct local pathway when the one or more user devices <NUM>, <NUM> are in close physical proximity to the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> to a pathway over network <NUM> when the one or more user devices <NUM>, <NUM> are farther from the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM>. In some examples, the system leverages GPS information from the one or more user devices <NUM>, <NUM> to determine whether the one or more user devices <NUM>, <NUM> are close enough to the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> to use the direct local pathway or whether the one or more user devices <NUM>, <NUM> are far enough from the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> that the pathway over network <NUM> is required. In other examples, the system leverages status communications (e.g., pinging) between the one or more user devices <NUM>, <NUM> and the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> to determine whether communication using the direct local pathway is possible. If communication using the direct local pathway is possible, the one or more user devices <NUM>, <NUM> communicate with the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> using the direct local pathway. If communication using the direct local pathway is not possible, the one or more user devices <NUM>, <NUM> communicate with the sensors <NUM>, the module <NUM>, the camera <NUM>, and the robotic devices <NUM> and <NUM> using the pathway over network <NUM>.

In some implementations, the system <NUM> provides end users with access to images captured by the camera <NUM> to aid in decision making. The system <NUM> may transmit the images captured by the camera <NUM> over a wireless WAN network to the user devices <NUM>, <NUM>. Because transmission over a wireless WAN network may be relatively expensive, the system <NUM> uses several techniques to reduce costs while providing access to significant levels of useful visual information.

Claim 1:
A method comprising:
obtaining (<NUM>), by a monitoring system, image data that depicts a portion of a property (<NUM>);
determining (<NUM>), by the monitoring system (<NUM>), that the image data depicts a human object;
based on determining, by the monitoring system, that the image data depicts the human object, determining (<NUM>), by the monitoring system, whether the depicted human object is located within an exclusionary region (<NUM>) of the property;
based on determining, by the monitoring system (<NUM>), that the depicted human object is not located within the exclusionary region of the property, triggering (<NUM>), by the monitoring system, an event based on the image data;
obtaining, by the monitoring system, different image data that depicts the portion of the property;
determining, by the monitoring system, that the different image data depicts a second human object;
based on determining, by the monitoring system, that the different image data depicts the second human object, determining, by the monitoring system, whether the depicted second human object is located within the exclusionary region of the property; and
based on determining, by the monitoring system, that a first portion of the depicted second human object is located within the exclusionary region of the property and a second portion of the depicted second human object is located outside of the exclusionary region, triggering, by the monitoring system, an event based on the different image data.