Abstract: A system and method for identifying observations using images of a construction site. A method includes identifying observations in visual media content by identifying items shown in the visual media content, wherein each identified observation corresponds to at least one item of the identified items, wherein each observation corresponds to a type; determining a likelihood impact parameter for each of the observations by applying likelihood rules based on a classification of each of the corresponding at least one item and a ratio of historical incidents of the same type as the observation to a total number of projects in a time period; determining a severity impact parameter for each of the observations by applying severity rules based on an average cost of the historical incidents of the same type as the observation; and determining at least one risk factor for each observation based on its likelihood and severity impact parameters.

Abstract: A system and method for identifying observations using images of a construction site. A method includes identifying observations in visual media content by identifying items shown in the visual media content, wherein each identified observation corresponds to at least one item of the identified items, wherein each observation corresponds to a type; determining a likelihood impact parameter for each of the observations by applying likelihood rules based on a classification of each of the corresponding at least one item and a ratio of historical incidents of the same type as the observation to a total number of projects in a time period; determining a severity impact parameter for each of the observations by applying severity rules based on an average cost of the historical incidents of the same type as the observation; and determining at least one risk factor for each observation based on its likelihood and severity impact parameters.

Abstract: A system and method for identifying hazardous site conditions. The method includes training a classifier using a labeled training set, wherein the classifier is trained to classify site conditions based on features extracted from enhanced floor plans, wherein the labeled training set includes a plurality of training features and a plurality of training labels, wherein the plurality of training features are extracted from a plurality of training enhanced floor plans, wherein the plurality of training labels are a plurality of hazardous site condition identification labels; and identifying at least one hazardous site condition of a test enhanced floor plan by applying the classifier to a plurality of test features extracted from the test enhanced floor plan, wherein the classifier outputs at least one site condition classification when applied to the plurality of test features, wherein the at least one hazardous site condition is identified based on the at least one site condition classification.

Abstract: A system and method for creating enhanced floor plans. The method includes converting visual multimedia content into a plurality of frames, wherein the visual multimedia content shows a site, wherein each frame is a two-dimensional (2D) image showing a portion of the site; generating, based on the plurality of frames, a sparse three-dimensional (3D) model of the site, wherein the sparse 3D model includes a point cloud; geo-localizing the sparse 3D model with respect to a site layout model by identifying a plurality of matching features of the site layout model with respect to the sparse 3D model; and creating an enhanced floor plan based on the geo-localization, wherein the enhanced floor plan includes a plurality of floor plan points of the site layout model associated with respective portions of the sparse 3D model.

Abstract: A system and method for identifying hazardous site conditions. The method includes training a classifier using a labeled training set, wherein the classifier is trained to classify site conditions based on features extracted from enhanced floor plans, wherein the labeled training set includes a plurality of training features and a plurality of training labels, wherein the plurality of training features are extracted from a plurality of training enhanced floor plans, wherein the plurality of training labels are a plurality of hazardous site condition identification labels; and identifying at least one hazardous site condition of a test enhanced floor plan by applying the classifier to a plurality of test features extracted from the test enhanced floor plan, wherein the classifier outputs at least one site condition classification when applied to the plurality of test features, wherein the at least one hazardous site condition is identified based on the at least one site condition classification.

Abstract: A system and method for creating enhanced floor plans. The method includes converting visual multimedia content into a plurality of frames, wherein the visual multimedia content shows a site, wherein each frame is a two-dimensional (2D) image showing a portion of the site; generating, based on the plurality of frames, a sparse three-dimensional (3D) model of the site, wherein the sparse 3D model includes a point cloud; geo-localizing the sparse 3D model with respect to a site layout model by identifying a plurality of matching features of the site layout model with respect to the sparse 3D model; and creating an enhanced floor plan based on the geo-localization, wherein the enhanced floor plan includes a plurality of floor plan points of the site layout model associated with respective portions of the sparse 3D model.