Abstract: This description describes a system for identifying individuals within a digital file. The system accesses a digital file describing the movement of unidentified individuals and detects a face for an unidentified individual at a plurality of locations in the video. The system divides the digital file into a set of segments and detects a face of an unidentified individual by applying a detection algorithm to each segment. For each detected face, the system applies a recognition algorithm to extract feature vectors representative of the identity of the detected faces which are stored in computer memory. The system applies a recognition algorithm to query the extracted feature vectors for target individuals by matching unidentified individuals to target individuals, determining a confidence level describing the likelihood that the match is correct, and generating a report to be presented to a user of the system.

Abstract: Aspects of the technology described herein optimally locate business labels within the footprint of a building shown on a digital map. An optimal arrangement comprises business labels displayed entirely within the building footprint without the business labels overlapping each other. The technology initially generates label arrangements and calculates a cost for the arrangements. A cost of zero means the arrangement is optimal. For non-zero costs, a lower cost means the arrangement is close to an optimal arrangement. The technology can continue to generate arrangements for analysis until an acceptable arrangement is found.

Abstract: Systems, methods, and computer-readable storage media are provided for aligning three-dimensional point clouds that each includes data representing at least a portion of an area-of-interest. The area-of-interest is divided into multiple regions, each region having a closed-loop structure defined by a plurality of border segments, each border segment including a plurality of fragments. Point clouds representing the fragments that make up each closed-loop region are aligned with one another in a parallelized manner, for instance, utilizing a Simultaneous Generalized Iterative Closest Point (SGICP) technique, to create aligned point cloud regions. Aligned point cloud regions sharing a common border segment portion are aligned with one another to create a single, consistent, aligned point cloud having data that accurately represents the area-of-interest.