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 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: 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 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: Computer vision and image characteristic search is described. The described system leverages visual search techniques by determining visual characteristics of objects depicted in images and comparing the determined characteristics to visual characteristics of other images, e.g., to identify similar visual characteristics in the other images. In some aspects, the described system performs searches that leverage a digital image as part of a search query to locate digital content of interest. In some aspects, the described system surfaces multiple user interface instrumentalities that include images of patterns, textures, or materials and that are selectable to initiate a visual search of digital content having a similar pattern, texture, or material. The described aspects also include pattern-based authentication in which the system determines authenticity of an item in an image based on a similarity of its visual characteristics to visual characteristics of known authentic items.

Abstract: Computer vision and image characteristic search is described. The described system leverages visual search techniques by determining visual characteristics of objects depicted in images and comparing the determined characteristics to visual characteristics of other images, e.g., to identify similar visual characteristics in the other images. In some aspects, the described system performs searches that leverage a digital image as part of a search query to locate digital content of interest. In some aspects, the described system surfaces multiple user interface instrumentalities that include images of patterns, textures, or materials and that are selectable to initiate a visual search of digital content having a similar pattern, texture, or material. The described aspects also include pattern-based authentication in which the system determines authenticity of an item in an image based on a similarity of its visual characteristics to visual characteristics of known authentic items.

Abstract: Computer vision for unsuccessful queries and iterative search is described. The described system leverages visual search techniques by determining visual characteristics of objects depicted in images and describing them, e.g., using feature vectors. In some aspects, these visual characteristics are determined for search queries that are identified as not being successful. Aggregated information describing visual characteristics of images of unsuccessful search queries is used to determine common visual characteristics and objects depicted in those images. This information can be used to inform other users about unmet needs of searching users. In some aspects, these visual characteristics are used in connection with iterative image searches where users select an initial query image and then the search results are iteratively refined.

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 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: 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 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 method includes, for each of two or more driving sessions in which a student driver operates a vehicle, gathering driving skill data indicative of at least one of behavior of the student driver, acceleration of the vehicle, braking of the vehicle, or steering of the vehicle, and generating a driving session report. The method further includes causing the driving session reports corresponding to the two or more driving sessions to be displayed to a driving instructor, and receiving comments from the driving instructor about the two or more driving sessions of the student driver. Still further, the method includes storing the driving session reports corresponding to the two or more driving sessions along with the received comments from the driving instructor.

Abstract: Computer vision and image characteristic search is described. The described system leverages visual search techniques by determining visual characteristics of objects depicted in images and comparing the determined characteristics to visual characteristics of other images, e.g., to identify similar visual characteristics in the other images. In some aspects, the described system performs searches that leverage a digital image as part of a search query to locate digital content of interest. In some aspects, the described system surfaces multiple user interface instrumentalities that include images of patterns, textures, or materials and that are selectable to initiate a visual search of digital content having a similar pattern, texture, or material. The described aspects also include pattern-based authentication in which the system determines authenticity of an item in an image based on a similarity of its visual characteristics to visual characteristics of known authentic items.

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: 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. The gaze location value may be generated by determining a location of the vehicle operator's gaze, determining which area of the vehicle is associated with the gaze location, and assigning the gaze location value based on the area of the vehicle associated with the gaze location. 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, one or more recommendations to improve vehicle operator performance may be identified and communicated to the vehicle operator.

Abstract: In a computer-implemented method, data about potential vehicle operator impairment is retrieved. The data is generated by monitoring a vehicle operator, the environment ahead of the vehicle, and/or force in one or more directions. A number of impairment scores are generated by analyzing the data about potential vehicle operator impairment. A specific time period during which the vehicle operator tends to be most impaired is determined based on the impairment scores. Recommendations to reduce operator impairment of the vehicle operator are identified and communicated to the vehicle operator.

Abstract: Computer vision and image characteristic search is described. The described system leverages visual search techniques by determining visual characteristics of objects depicted in images and comparing the determined characteristics to visual characteristics of other images, e.g., to identify similar visual characteristics in the other images. In some aspects, the described system performs searches that leverage a digital image as part of a search query to locate digital content of interest. In some aspects, the described system surfaces multiple user interface instrumentalities that include images of patterns, textures, or materials and that are selectable to initiate a visual search of digital content having a similar pattern, texture, or material. The described aspects also include pattern-based authentication in which the system determines authenticity of an item in an image based on a similarity of its visual characteristics to visual characteristics of known authentic items.

Abstract: Computer vision for unsuccessful queries and iterative search is described. The described system leverages visual search techniques by determining visual characteristics of objects depicted in images and describing them, e.g., using feature vectors. In some aspects, these visual characteristics are determined for search queries that are identified as not being successful. Aggregated information describing visual characteristics of images of unsuccessful search queries is used to determine common visual characteristics and objects depicted in those images. This information can be used to inform other users about unmet needs of searching users. In some aspects, these visual characteristics are used in connection with iterative image searches where users select an initial query image and then the search results are iteratively refined.

Abstract: A method includes, during a driving session in which a student driver operates a vehicle, gathering driving skill data indicative of at least one of behavior of the student driver, acceleration of the vehicle, braking of the vehicle, or steering of the vehicle, and gathering comments from a driving instructor about the driving session. The method also includes generating a driving session report corresponding to the driving session. The driving session report includes at least one score based on the driving skill data, and the comments from the driving instructor about the driving session. Still further, the method includes causing the driving session report to be displayed on a display device.