A system, method, and computer-readable storage medium are disclosed that execute machine vision operations to categorize a locality. At least one embodiment accesses a map image of a locality, where the map image includes geographical artefacts corresponding to entities within the locality; analyzes the map image to detect the entities in the locality using the geographical artefacts; assigns entity classes to detected entities in the locality; assigns a locality score to the locality based on entity classes included in the locality; retrieves street view images for one or more of the detected entities in the locality; and analyzes street view images of the detected entities to assign one or more further classifications to the detected entities. Other embodiments include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the method.

Systems, computer program products, and methods are described herein for providing efficient retrieval of business valuation information. The present invention is configured to receive, via a user device, information associated with a first business; retrieve from a business classification database, a business classification code; automatically retrieve, from a valuation database, one or more business names; determine a similarity metric between the first business and each of the one or more business names; retrieve, from the valuation database, one or more business valuations associated with the one or more business names; initiate a dashboard report script, wherein the dashboard report script is configured to display the one or more business names with corresponding information, including the one or more business valuations associated with the one or more business names.

A method includes confirming when a vehicle accesses a region of interest, obtaining data associated within the region of interest, and determining, based on analytics performed on the data obtained of the region of interest, whether one or more anomalies are present at the region of interest. Obtaining data includes at least one of collecting, with an imaging sensor associated with the vehicle, image data of a given point of interest within the region of interest or collecting, with a motion sensor associated with the vehicle, motion data of the vehicle in a given fragment of interest within the region of interest. The confirming, obtaining and determining steps are performed by at least one processing device comprising a processor operatively coupled to a memory.

A technique is introduced for utilizing data associated with a monitored premises to determine a likelihood of a crime, or other activity, occurring at the premises. In an example embodiment, premises data is received from one or more sources including sensor devices located at the premises and other data sources including third-party databases. The premises data is processed using a machine learning model, such as an artificial neural network, to generate a risk score that is indicative of the likelihood of a crime occurring at the premises in real-time or in the future. The introduced technique for risk evaluation can be implemented in conjunction with a premises security system, for example, to route alarms generated by monitoring devices located at the premises.

In one embodiment, a method includes accessing an image of a physical world scene, detecting a number of straight-line segments in the accessed image, identifying a first vanishing point and a second vanishing point in the image, where each vanishing point corresponds to a sub-set of the number of straight-line segments, and where the first vanishing point and the second vanishing point are orthogonal, identifying a planar region in the accessed image represented by one or more straight-line segments associated with the first vanishing point and one or more straight-line segments associated with the second vanishing point, transforming a virtual object associated with the planar region based on one or more properties associated with the planar region, and displaying the transformed virtual object over the image.

A system and computer-implemented method include a wireless network hub configured to forward received sensor readings to a sensor analysis system. One or more sensor units coupled to the wireless network hub and affixed to a structure are configured to wirelessly transmit data to the wireless network hub at a first time frequency, and, in response to a detected danger to the structure, wirelessly transmit sensor readings to the wireless network hub at a second time frequency greater than the first time frequency.

In one embodiment, a method includes accessing an image of a physical world scene, detecting a number of straight-line segments in the accessed image, identifying a first vanishing point and a second vanishing point in the image, where each vanishing point corresponds to a sub-set of the number of straight-line segments, and where the first vanishing point and the second vanishing point are orthogonal, identifying a planar region in the accessed image represented by one or more straight-line segments associated with the first vanishing point and one or more straight-line segments associated with the second vanishing point, transforming a virtual object associated with the planar region based on one or more properties associated with the planar region, and displaying the transformed virtual object over the image.

In variants, the method for property condition analysis can include: determining a measurement, optionally determining a set of property attributes, determining a condition score, optionally providing the condition score, and optionally training a condition scoring model.

A system and method is provided for augmenting an image with stylized features. An exemplary method includes identifying, in a first image, a first version of an object having a first set of graphical features and identifying, in a second image, a second version of the object having a second set of graphical features. Moreover, the method includes extracting the first and second sets of graphical features from the first and second images, respectively, and generating a third set of graphical features by calculating differences between the first and second sets of graphical features. Finally, using the third set of graphical features, the method includes augmenting the first version of the object in the first image.

Commentary rating determination systems and methods determine a commentary rating for commentary about a subject media content event that has been generated by a community member. An exemplary embodiment receives video information acquired by a 360 video camera, identifies a physical object from the received video information, determines a physical attribute associated with the identified physical object, wherein the determined physical attribute describes a characteristic of the identified physical object, compares the determined physical attribute of the identified physical object with a plurality of predefined physical object attributes stored in a database, and in response to identifying one of the plurality of predefined physical object attributes that matches the determined physical attribute, associates the quality value of the identified one of the plurality of predefined physical object attributes with the identified physical object. Then, the commentary rating is determined for the commentary based on the associated quality value.