Abstract: The present invention is a system and method for delivering optimized road maintenance analysis to a municipality. The instant innovation scans roadways for distressed street surfaces, damaged signage, and other less-than-optimal municipal assets. Data is collected by multiple municipal fleet vehicles as such vehicles drive upon roads within a municipality. Collected data are analyzed by a machine learning algorithm using criteria that most directly correspond to multi-year road quality predictions. The instant innovation provides to a user one or more suggestions and scenario results for roadway maintenance strategies based upon the data analysis.

Abstract: In one embodiment, a method for detecting faces in video image frames includes comparing a current image frame to a previously processed image frame to determine similarity, discarding the current image frame if the current image frame and the previously processed image frame are, detecting at least one detected facial image in the current image frame, comparing the at least one detected facial image to at least one most recently stored facial image stored in a most recently used (MRU) cache to determine similarity, discarding the at least one detected facial image if the at least one detected facial image and the at least one most recently stored facial image are similar; and storing the at least one detected facial image in the MRU cache if the at least one detected facial image and the at least one most recently stored facial image are not similar.

Abstract: In one embodiment, a method for detecting faces in video image frames includes comparing a current image frame to a previously processed image frame to determine similarity, discarding the current image frame if the current image frame and the previously processed image frame are, detecting at least one detected facial image in the current image frame, comparing the at least one detected facial image to at least one most recently stored facial image stored in a most recently used (MRU) cache to determine similarity, discarding the at least one detected facial image if the at least one detected facial image and the at least one most recently stored facial image are similar; and storing the at least one detected facial image in the MRU cache if the at least one detected facial image and the at least one most recently stored facial image are not similar.

Abstract: A method and system for audience segmentation is described, the method and system including preparing a plurality of guidebooks of prior probability distributions for content items and user profile attributes, the prior probabilities and user profile attributes being extractable from within audience measurement data, receiving raw audience measurement data, analyzing, at a processor, the received raw audience measurement data using the prepared plurality of guidebooks, generating a plurality of clusters of data per user household as a result of the analyzing, correlating viewing activity to each cluster within an identified household, predicting a profile of a viewer corresponding to each cluster within the identified household, applying classifier rules in order to assign viewing preference tags to each predicted profile, and assigning each predicted profile viewing preferences based on the viewing preference tags assigned to that profile Related systems, methods, and apparatus are also described.