Abstract:
A damage assessment module operating on a computer system automatically evaluates a roof, estimating damage to the roof by analyzing a point cloud of a roof. The damage assessment module identifies individual shingles from the point cloud and detects potentially damaged areas on each of the shingles. The damage assessment module then maps the potentially damaged areas of each shingle back to the point cloud to determine which areas of the roof are damaged. Based on the estimation, the damage assessment module generates a report on the roof damage.
Abstract:
A damage assessment module operating on a computer system automatically evaluates a roof, estimating damage to the roof by analyzing a point cloud of a roof. The damage assessment module identifies individual shingles from the point cloud and detects potentially damaged areas on each of the shingles. The damage assessment module then maps the potentially damaged areas of each shingle back to the point cloud to determine which areas of the roof are damaged. Based on the estimation, the damage assessment module generates a report on the roof damage.
Abstract:
In an embodiment, movement-data is gathered with one or more sensors (e.g., accelerometers, GPS receivers, etc.) during a driver's driving session. A score may be calculated for the driving session, and the driver's progress is evaluated by a driver-evaluation system. A driving session report or graphical user-interface (GUI) is generated with a computer processor and displayed at a display device. The displayed report or GUI includes a graphic representing the driver's progress relative to historical data.
Abstract:
The method, system, and computer-readable medium facilitates monitoring one or more eyes of a vehicle operator during a driving session to generate a plurality of gaze location logs with gaze location values and timestamps. The gaze location value may be generated by determining a focal point of the vehicle operator's gaze, determining which of a plurality of areas of the vehicle is associated with the focal point, and assigning the gaze location value based on the area of the vehicle associated with the focal point. The gaze location logs may be analyzed to determine the duration of the vehicle operator's gaze at each area of the vehicle. Based on the duration of the vehicle operators gaze, recommendations to improve vehicle operator performance may be determined and communicated to the vehicle operator.
Abstract:
A damage assessment module operating on a computer system automatically evaluates a property, estimating damage to the property by analyzing a point cloud of a property. The damage assessment module identifies individual point clusters or segments from the point cloud and detects potentially damaged areas of the property surface by identifying outlier points in the point clusters. The damage assessment module may be used to determine the financial cost of the damage and/or determine whether the property should be replaced or repaired. In addition to eliminating the need for an estimator to visit the property in person, the damage assessment module improves the consistency and accuracy associated with estimating damage to a property.
Abstract:
During driving sessions, data may be collected via one or more sensors that are incorporated within a vehicle or as part of a device carried within the vehicle. Using this data, a driving session report may be generated and a driving session feedback score may be calculated, which provides feedback regarding a students' driving skills Driver profiles may be generated for each student including contact information and/or any number of driving session reports saved over the course of several driving sessions. A user interface is described that facilitates interaction by allowing a user to create driver profiles, group driver profiles, display driver profiles as a single list view or as a grouped list view, select driver profiles from these displayed lists, edit driver information and/or delete driver profiles, and display driving session reports stored as part of a driver profile together such that comparisons may be made.
Abstract:
In an embodiment, movement-data is gathered with one or more sensors (e.g., accelerometers, GPS receivers, etc.) during a driver's driving session. A score may be calculated for the driving session, and the driver's progress is evaluated by a driver-evaluation system. A driving session report or graphical user-interface (GUI) is generated with a computer processor and displayed at a display device. The displayed report or GUI includes a graphic representing the driver's progress relative to historical data.
Abstract:
A damage assessment module operating on a computer system automatically evaluates a property, estimating damage to the property by analyzing a point cloud of a property. The damage assessment module identifies individual point clusters or segments from the point cloud and detects potentially damaged areas of the property surface by identifying outlier points in the point clusters. The damage assessment module may be used to determine the financial cost of the damage and/or determine whether the property should be replaced or repaired. In addition to eliminating the need for an estimator to visit the property in person, the damage assessment module improves the consistency and accuracy associated with estimating damage to a property.
Abstract:
In an embodiment, movement-data is gathered with one or more sensors (e.g., accelerometers, GPS receivers, etc.) during a driver's driving session. A score may be calculated for the driving session, and the driver's progress is evaluated by a driver-evaluation system. A driving session report or graphical user-interface (GUI) is generated with a computer processor and displayed at a display device. The displayed report or GUI includes a graphic representing the driver's progress relative to historical data.
Abstract:
A gaze tracking system captures images of a vehicle operator. The gaze tracking system may detect facial features in the images and track the position of the facial features over time. The gaze tracking system may detect a triangle in an image, wherein the vertices of the triangle correspond to the facial features. The gaze tracking system may analyze the detected triangle to identify a surface normal for the triangle, and may track the surface normal (e.g., across multiple images) to track the eye gaze direction of the driver over time. The images may be captured and analyzed in near-real time. By tracking movement of the driver's head and eyes over time, the gaze analysis system may predict or estimate head position and/or gaze direction when one or more facial features are not detectable.