One example system comprises a LIDAR sensor that rotates about an axis to scan an environment of the LIDAR sensor. The system also comprises one or more cameras that detect external light originating from one or more external light sources. The one or more cameras together provide a plurality of rows of sensing elements. The rows of sensing elements are aligned with the axis of rotation of the LIDAR sensor. The system also comprises a controller that operates the one or more cameras to obtain a sequence of image pixel rows. A first image pixel row in the sequence is indicative of external light detected by a first row of sensing elements during a first exposure time period. A second image pixel row in the sequence is indicative of external light detected by a second row of sensing elements during a second exposure time period.

One example system comprises a LIDAR sensor that rotates about an axis to scan an environment of the LIDAR sensor. The system also comprises one or more cameras that detect external light originating from one or more external light sources. The one or more cameras together provide a plurality of rows of sensing elements. The rows of sensing elements are aligned with the axis of rotation of the LIDAR sensor. The system also comprises a controller that operates the one or more cameras to obtain a sequence of image pixel rows. A first image pixel row in the sequence is indicative of external light detected by a first row of sensing elements during a first exposure time period. A second image pixel row in the sequence is indicative of external light detected by a second row of sensing elements during a second exposure time period.

A method for constructing a three-dimensional road network map is disclosed. The method includes: extracting a two-dimensional road based on a satellite remote sensing image; skeletonizing the two-dimensional road to obtain a two-dimensional road network map; and determining a height of each point in the two-dimensional road network map based on an elevation of three-dimensional point cloud data, to obtain the three-dimensional road network map.

A method for constructing a three-dimensional road network map is disclosed. The method includes: extracting a two-dimensional road based on a satellite remote sensing image; skeletonizing the two-dimensional road to obtain a two-dimensional road network map; and determining a height of each point in the two-dimensional road network map based on an elevation of three-dimensional point cloud data, to obtain the three-dimensional road network map.

Methods and systems for assessing property based on predictive analytics techniques that use external data are described herein. A server may identify a reference set of information for a reference property evaluated with a reference risk score in accordance with a risk score rule that meets a predetermined threshold. The server may obtain an external data file from an external data source, wherein the external data file includes an external set of information for a prospective property. The server may compare the reference set of information with the external set of information to identify a common feature, condition, or attribute, and if identified, may evaluate the prospective property by determining a predicted risk score based on the external set of information in accordance with the risk score rule. If the predicted risk score is determined to meet the threshold, the server may indicate the prospective property as pre-approved.

Methods and systems for assessing property based on predictive analytics techniques that use external data are described herein. A server may identify a reference set of information for a reference property evaluated with a reference risk score in accordance with a risk score rule that meets a predetermined threshold. The server may obtain an external data file from an external data source, wherein the external data file includes an external set of information for a prospective property. The server may compare the reference set of information with the external set of information to identify a common feature, condition, or attribute, and if identified, may evaluate the prospective property by determining a predicted risk score based on the external set of information in accordance with the risk score rule. If the predicted risk score is determined to meet the threshold, the server may indicate the prospective property as pre-approved.

A system and method for determining a viewpoint of a traffic camera includes obtaining images of a real road captured by the traffic camera, segmenting a road surface from the captured images to generate a mask of the real road, generating a 3D model of a simulated road corresponding to the real road, from geographical data of the real road, adding a simulated camera corresponding to the traffic camera to a location in the 3D model that is corresponding to a location of the traffic camera in the real road, generating a plurality of simulated images of the simulated road using the 3D model, each corresponding to a set of viewpoint parameters of the simulated traffic camera, selecting the simulated image that provides the best fit between the simulated image and the mask, and generating mapping between pixel locations in the captured images and locations on the real road.

A system and method for determining a viewpoint of a traffic camera includes obtaining images of a real road captured by the traffic camera, segmenting a road surface from the captured images to generate a mask of the real road, generating a 3D model of a simulated road corresponding to the real road, from geographical data of the real road, adding a simulated camera corresponding to the traffic camera to a location in the 3D model that is corresponding to a location of the traffic camera in the real road, generating a plurality of simulated images of the simulated road using the 3D model, each corresponding to a set of viewpoint parameters of the simulated traffic camera, selecting the simulated image that provides the best fit between the simulated image and the mask, and generating mapping between pixel locations in the captured images and locations on the real road.

Techniques are described for configuring a monitoring system to assist users during a detected emergency condition at a property. In some implementations, sensor data from one or more sensors that are located at the property are obtained by a monitoring system that is configured to monitor the property. A determination that there is an emergency condition at the property is made by the monitoring system based on the sensor data, determining. A location of a person inside the property is determined by the monitoring system based on the sensor data. A first path to the person and a second path to guide the person away from the emergency condition are determined by the monitoring system. The first path to the person and the second path to guide the person away from the emergency condition are navigated by a computing device of the monitoring system.

Techniques are described for configuring a monitoring system to assist users during a detected emergency condition at a property. In some implementations, sensor data from one or more sensors that are located at the property are obtained by a monitoring system that is configured to monitor the property. A determination that there is an emergency condition at the property is made by the monitoring system based on the sensor data, determining. A location of a person inside the property is determined by the monitoring system based on the sensor data. A first path to the person and a second path to guide the person away from the emergency condition are determined by the monitoring system. The first path to the person and the second path to guide the person away from the emergency condition are navigated by a computing device of the monitoring system.