Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing video controlled adjustment of light conditions at a property. A monitoring system obtains video data from a video recording device at the property and uses the video data to determine a location of a person at the property as well as a location of an electronic window treatment at the property. Using the video data, the system identifies an attribute of light entering a window at the property. The system determines an adjustment setting for the electronic window treatment at the property based on the attribute of the light and the location of the person at the property. Based on the adjustment setting, a command is provided to perform a first adjustment action that adjusts the position of the electronic window treatment located at the window.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for location tracking. In some implementations, a corresponding method includes obtaining images of one or more persons within a property; identifying a heartbeat for each person of the one or more persons within the images; identifying a location for each person within the images; receiving a request that indicates a heartbeat signature generated from heartbeats sensed by a device worn by a user; determining that an identified heartbeat of a person of the one or more persons matches the heartbeat signature; in response to determining that the identified heartbeat of the person of the one or more persons matches the heartbeat signature, selecting the person as the user; and in response to selecting the person as the user, providing a response to the request based on a location of the person.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, are described for implementing intelligent seating for wellness monitoring. A system obtains data from a first sensor integrated in an intelligent seating apparatus at a property. The first data indicates a potential abnormal condition of a person at the property. The system determines that the person has an abnormal condition based on the first data corresponding to the person having used the seating apparatus. Based on the abnormal condition, the system provides an indication to a client device of the person to prompt the person to adjust their use of the seating apparatus. The system also obtains visual indications of the abnormal condition, determines the type of abnormal condition afflicting the person, and determines a wellness command with instructions for alleviating the abnormal condition. The wellness command is provided for display on the client device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for finding lost objects. In some implementations, an unassociated object that appeared in a video from a property is identified. Known entities for the property are identified. A number of times that the known entities appeared in videos from the property is obtained. An order to display the known entities for the property based on a number of times that the known entities appeared in videos from the property are determined. An indication that the unassociated object is associated with a particular entity of the known entities is received. An image of the unassociated object from the video in association with the particular entity of the known entities is stored.

Abstract: Methods and systems including computer programs encoded on a computer storage medium, for obtaining imaging data of a parking lot that includes a set of parking spots, detecting a vehicle enter the parking lot, generating a vehicle recognition model for the vehicle, determining that the vehicle is parked in a parking spot, detecting a customer exit the vehicle, generating a customer recognition model for the customer, determining that the customer has entered a business of one or more businesses affiliated with the parking lot, and providing information related to parking space usage for the parking spot and the business to a user device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for monitoring of pet feeding. The methods, systems, and apparatus include actions of: obtaining a first reference image of a container corresponding to a full state of the container; obtaining a second reference image of the container corresponding to an empty state of the container; obtaining a sample image of the container; based on the first and second reference images, determining an amount of content in the container from the sample image; and based on the amount of the content being less than a reference amount, notifying a user that the amount of the content is getting low.

Abstract: Methods and apparatus are disclosed for enhancing urban surface model with image data obtained from a satellite image. Three dimensional models of an urban cityscape obtained from digital surface models may comprise surface location information but lack image information associated with the cityscape, such as the color and texture of building facades. The location of the satellite at the time of recording the satellite image interest may be obtained from metadata associated with the satellite image. A 3D model of a cityscape corresponding to the satellite image may be subjected to a transformation operation to determine portions of the 3D model that are viewable from a location corresponding to the location of the satellite when taking the picture. Visible facades buildings of the 3D model ma be identified and mapped to portions of the satellite image which may then be used in rendering 2D images from the 3D model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting people for a training set. The methods, systems, and apparatus include actions of: obtaining an image of a user, obtaining an initial training set that includes the image of the user as a positive example and images of a subset of a set of other people as negative examples, training an initial classifier with the images of the initial training set, determining false positive classifications by the initial classifier, selecting people in the set of other people based on the false positive classifications, obtaining an updated training set that includes an image of the user, images of the subset of the set of other people, and images of the people that are selected, and generating an updated classifier with the updated training set.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for cooperative video surveillance. The methods, systems, and apparatus include actions of determining that a vehicle has arrived at a particular parking spot, determining a view of a property for an onboard camera for the vehicle, providing a detection rule to the vehicle based on the view of the property for the onboard camera for the vehicle, and receiving an image captured by the onboard camera for the vehicle based on satisfaction of the detection rule.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for canine assisted home monitoring. The methods, systems, and apparatus include actions of: obtaining a reference signal from an animal at a property; determining whether an event occurred at the property corresponding to when the reference signal from the animal was received; in response to a determination that the event occurred at the property corresponding to when the reference signal from the animal was received, determining that the reference signal indicates that the event is likely occurring at the property; obtaining a sample signal from the animal at the property; determining whether the sample signal corresponds to the reference signal; and notifying a user that the event, which was determined to be indicated by the reference signal, is likely occurring again at the property.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating distributed jobs for cameras in a monitored property. The methods, systems, and apparatus include actions of obtaining a request to process a video based on an event detected by a first camera at a monitored property, determining resources likely to be available corresponding to the other cameras at the monitored property, allocating one or more tasks corresponding to processing the video to the other cameras based on the resources likely to be available corresponding to the other cameras, and providing the one or more allocated tasks to the first camera and to the other cameras.

Abstract: A computer-implemented method includes obtaining an image of an area of a property from an augmented reality device, identifying the area of the property based on the image obtained from the augmented reality device, determining that the area of the property corresponds to an event at the property or a configuration of a monitoring system of the property, and providing, in response to determining that the area of the property corresponds to the event or the configuration, information that represents the event or the configuration and that is configured to be displayed on the augmented reality device.

Abstract: Methods, and systems including computer programs encoded on a computer storage medium, for training a detection model for surveillance devices using semi-supervised learning. In one aspect, the methods include receiving imaging data collected by a camera of a scene within a field of view of the camera. Annotated training data is generated from the imaging data and one or more detection models are trained using the annotated training data. Based on a set of performance parameters, an optimized detection model is selected of the one or more detection models, and the optimized detection model is provided to the camera.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an event detector. The methods, systems, and apparatus include actions of obtaining frames of a video, determining whether an object of interest is detected within the frames, determining whether motion is detected within the frames, determining whether the frames correspond to motion by an object of interest, generating a training set that includes labeled inter-frame differences based on whether the frames correspond to motion by an object of interest, and training an event detector using the training set.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for multi-query object matching based on inverse model frequency. The methods, systems, and apparatus include actions of obtaining images of a sample object, obtaining models of known objects, determining an image score for each pair of the images and the models, determining an inverse model frequency for each image based on the image scores, determining a model score for each model based on the inverse model frequencies and the image scores, and selecting a particular known object of the known objects as the sample object based on the model scores.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for monitoring system with a video analytic enhanced pet door. The methods, systems, and apparatus include actions of obtaining video from a camera, determining from the video that an object is approaching the camera, in response to determining from the video that an object is approaching the camera, determining whether the object is an animal, in response to determining that the object is an animal, determining from the video whether the animal is authorized to enter a home, and in response to determining from the video that the animal is authorized to enter the home, opening a pet door.

Abstract: An electronic peep hole device includes a first portion that is configured to be mounted to an exterior side of a front door of a monitored property, the first portion includes a user interface and a camera that is configured to capture image data, a second portion that is configured to be mounted to an interior side of the front door of the monitored property, the second portion includes a display unit that is configured to display the image data captured by the camera, and a connecting portion that is configured to connect the first portion to the second portion through a hole in the surface of the front door, the connecting portion being configured to house an electrical connection between the first portion and the second portion.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for classifying actions of an object. The methods, systems, and apparatus include actions of: obtaining frames of video including an object of interest; determining a type of action of the object in each of the frames of video; determining a group of frames from the frames of video based on the type of action; determining an aggregated background subtraction (ABS) image based on adjacent frames of the group of frames; generating a training set that includes labeled ABS images including the ABS image; and training an action classifier using the training set.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining a foreground occupancy map for a camera view. The methods, systems, and apparatus include actions of determining an area of an image in which there is a false detection of an object, determining a likely contribution of the area to the false detection based on the foreground occupancy map, generating a modified object detector based on the likely contribution of the area, and detecting an object using the modified object detector.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for machine learning for home understanding and notification. In one aspect, a method includes obtaining reference videos from a camera within a home, determining from the reference videos that a particular person routinely leaves the home with a particular object at a particular time of day, determining from a sample video from the camera within the home that the particular person appears to be leaving the home without the particular object at the particular time of day, and in response, providing a notification regarding the particular object.