Abstract: Introduced here computer programs and associated computer-implemented techniques for establishing the dimensions of interior spaces. These computer programs are able to accomplish this by combining knowledge of these interior spaces with spatial information that is output by an augmented reality (AR) framework. Such an approach allows two-dimensional (2D) layouts to be seamlessly created through guided corner-to-corner measurement of interior spaces.

Abstract: Introduced here computer programs and associated computer-implemented techniques for generating measurements of physical structures and environments in an automated matter through analysis of data that is generated by one or more sensors included in a computing device. This can be accomplished by combining insights that are derived through analysis different types of data that are generated, computed, or otherwise obtained by a computing device. For instance, a computer program may enable or facilitate measurement of arbitrary dimensions, angles, and square footage of a physical structure based on (i) images generated by an image sensor included in the corresponding computing device and (ii) measurements generated by an inertial sensor included in the corresponding computing device.

Abstract: A computer system and method for performing property inspections. Digital media is received in a computer vision image analysis system from one or more user devices via a network and a determination is made regarding an environment type associated with the received digital media. One or more objects are determined that are located in the determined environment and which are present in the received digital media. A determination is made regarding an absence of objects in the received digital media contingent upon the determined environment type based upon a set of rules.

Abstract: Introduced here computer programs and associated computer-implemented techniques for modeling interior spaces based on an analysis of digital images of those interior spaces. These computer programs can be trained to accomplish this without using extensive sets of labeled data. Instead, these computer programs are able to effectively supplement labeled data with unlabeled data to accurately model interior spaces in settings where limited labeled data is available. Such an approach allows these computer programs to establish the layouts of interior spaces without extensive knowledge of those interior spaces and without users, who are responsible for generating the digital images, interacting with the surroundings in a meaningful way.

Abstract: Introduced here computer programs and associated computer-implemented techniques for generating measurements of physical structures and environments in an automated matter through analysis of data that is generated by one or more sensors included in a computing device. This can be accomplished by combining insights that are derived through analysis different types of data that are generated, computed, or otherwise obtained by a computing device. For instance, a computer program may enable or facilitate measurement of arbitrary dimensions, angles, and square footage of a physical structure based on (i) images generated by an image sensor included in the corresponding computing device and (ii) measurements generated by an inertial sensor included in the corresponding computing device.

Abstract: Methods, systems, and devices for generating a training set and using the training set to train an artificial intelligence algorithm to detect and blur faces in images of an interior space are described. An example method for generating a training set includes selecting a first image depicting an interior of a room, selecting a second image depicting at least a face of a person, generating, based on a transparency parameter and a roughness parameter, a semi-transparent surface image, selecting an illumination parameter to configure a first illumination level for the first image and a second illumination level for the second image, and generating a first composite image of the training data set by combining the illumination parameter, the first image, the second image, and the semi-transparent surface image.

Abstract: Introduced here computer programs and associated computer-implemented techniques for establishing the dimensions of interior spaces. These computer programs are able to accomplish this by combining knowledge of these interior spaces with spatial information that is output by an augmented reality (AR) framework. Such an approach allows two-dimensional (2D) layouts to be seamlessly created through guided corner-to-corner measurement of interior spaces.

Abstract: Introduced here computer programs and associated computer-implemented techniques for modeling interior spaces based on an analysis of digital images of those interior spaces. These computer programs can be trained to accomplish this without using extensive sets of labeled data. Instead, these computer programs are able to effectively supplement labeled data with unlabeled data to accurately model interior spaces in settings where limited labeled data is available. Such an approach allows these computer programs to establish the layouts of interior spaces without extensive knowledge of those interior spaces and without users, who are responsible for generating the digital images, interacting with the surroundings in a meaningful way.

Abstract: A computer system and method for performing property inspections. Digital media is received in a computer vision image analysis system from one or more user devices via a network and a determination is made regarding an environment type associated with the received digital media. One or more objects are determined that are located in the determined environment and which are present in the received digital media. A determination is made regarding an absence of objects in the received digital media contingent upon the determined environment type based upon a set of rules.

Abstract: Introduced here are computer programs and associated computer-implemented techniques for generating top-down models of interior spaces based on analysis of digital images of those interior spaces. These computer programs may permit individuals to utilize conventional computing devices to record imagery of interior spaces for the purpose of depth mapping (also referred to as “height mapping”). The end result—namely, the top-down models—may be similar to the digital elevation models that are commonly generated to represent elevation.

Abstract: Introduced here computer programs and associated computer-implemented techniques for establishing the dimensions of interior spaces. These computer programs are able to accomplish this by combining knowledge of these interior spaces with spatial information that is output by an augmented reality (AR) framework. Such an approach allows two-dimensional (2D) layouts to be seamlessly created through guided corner-to-corner measurement of interior spaces.

Abstract: Methods, systems, and devices for generating a training set and using the training set to train an artificial intelligence algorithm to detect and blur faces in images of an interior space are described. An example method for generating a training set includes selecting a first image depicting an interior of a room, selecting a second image depicting at least a face of a person, generating, based on a transparency parameter and a roughness parameter, a semi-transparent surface image, selecting an illumination parameter to configure a first illumination level for the first image and a second illumination level for the second image, and generating a first composite image of the training data set by combining the illumination parameter, the first image, the second image, and the semi-transparent surface image.

Abstract: A computer system and method for performing property inspections. Digital media is received in a computer vision image analysis system from one or more user devices via a network and a determination is made regarding an environment type associated with the received digital media. One or more objects are determined that are located in the determined environment and which are present in the received digital media. A determination is made regarding an absence of objects in the received digital media contingent upon the determined environment type based upon a set of rules.