Abstract: In one embodiment, a method includes accessing a point cloud comprising a plurality of point-cloud points, each point-cloud point corresponding to a location on a surface of an object located in a region in a three-dimensional space, identifying, from the point cloud, a plurality of point clusters, each point cluster comprising a plurality of point-cloud points located within a grid segment on a two-dimensional grid derived from the three-dimensional space, selecting, for each point cluster, a set of point-cloud points from the plurality of point-cloud points in the point cluster, the set of point-cloud points being selected based on a predetermined threshold number of point-cloud points associated with an acceptable reduction in an error detection rate, and determining, for each point cluster, a structure classification based on the selected set of point-cloud points from the point cluster.

Abstract: In one embodiment, a method includes accessing a point cloud comprising a plurality of point-cloud points, each point-cloud point corresponding to a location on a surface of an object located in a region in a three-dimensional space, identifying, from the point cloud, a plurality of point clusters, each point cluster comprising a plurality of point-cloud points located within a grid segment on a two-dimensional grid derived from the three-dimensional space, selecting, for each point cluster, a set of point-cloud points from the plurality of point-cloud points in the point cluster, the set of point-cloud points being selected based on a predetermined threshold number of point-cloud points associated with an acceptable reduction in an error detection rate, and determining, for each point cluster, a structure classification based on the selected set of point-cloud points from the point cluster.

Abstract: Embodiments are disclosed for improving cache or memory efficiency of a social network system. A method according to some embodiments includes steps of: receiving an instruction to improve cache or memory efficiency of social graph data of a social graph; generating based on the social graph a partitioning tree including multiple bottom-level buckets, the partitioning tree dividing the vertices of the social graph into the bottom-level buckets and ordering the bottom-level buckets such that a social network metric regarding the vertices is optimized; assigning user IDs to the vertices of the social network in a numerical sequence based on the ordering of the bottom-level buckets; storing the social graph data of the users in storage locations in an order according to the numeral sequence of the assigned user IDs of the vertices.

Abstract: Embodiments are disclosed for improving cache or memory efficiency of a social network system. A method according to some embodiments includes steps of: receiving an instruction to improve cache or memory efficiency of social graph data of a social graph; generating based on the social graph a partitioning tree including multiple bottom-level buckets, the partitioning tree dividing the vertices of the social graph into the bottom-level buckets and ordering the bottom-level buckets such that a social network metric regarding the vertices is optimized; assigning user IDs to the vertices of the social network in a numerical sequence based on the ordering of the bottom-level buckets; storing the social graph data of the users in storage locations in an order according to the numeral sequence of the assigned user IDs of the vertices.