公开(公告)号：US20230351697A1

公开(公告)日：2023-11-02

申请号：US17661193

申请日：2022-04-28

Applicant: Apple Inc.

Inventor： Khaled Mammou ,  Adrian A Biagioli ,  Deepak S Tolani

IPC: G06T17/20 ,  G06T7/64 ,  G06T19/00

CPC classification number: G06T17/205 ,  G06T7/64 ,  G06T19/00 ,  G06T2207/20021 ,  G06T2219/008 ,  G06T2210/21

Abstract: A method of decomposing a three-dimensional representation of an object into a plurality of convex hulls can include instantiating a cluster priority queue in a computing system memory that initially contains a cluster corresponding to the three-dimensional representation of the object, computing with a processor of the computing system a concavity measure for each cluster in the cluster priority queue, and, for the cluster with the highest concavity measure: (1) computing with the processor a cut plane that divides the cluster corresponding to the three-dimensional representation of the object into two new clusters, each of the two new clusters having a corresponding convex hull, wherein computing a cut plane includes performing a hierarchical search of potential cut planes, (2) removing the cluster corresponding to the three-dimensional representation of the object from the cluster priority queue, and (3) adding the two new clusters to the cluster priority queue.

公开(公告)号：US12293463B2

公开(公告)日：2025-05-06

申请号：US17661193

申请日：2022-04-28

Applicant: Apple Inc.

Inventor： Khaled Mammou ,  Adrian A Biagioli ,  Deepak S Tolani

IPC: G06T17/20 ,  G06T7/64 ,  G06T19/00

Abstract: A method of decomposing a three-dimensional representation of an object into a plurality of convex hulls can include instantiating a cluster priority queue in a computing system memory that initially contains a cluster corresponding to the three-dimensional representation of the object, computing with a processor of the computing system a concavity measure for each cluster in the cluster priority queue, and, for the cluster with the highest concavity measure: (1) computing with the processor a cut plane that divides the cluster corresponding to the three-dimensional representation of the object into two new clusters, each of the two new clusters having a corresponding convex hull, wherein computing a cut plane includes performing a hierarchical search of potential cut planes, (2) removing the cluster corresponding to the three-dimensional representation of the object from the cluster priority queue, and (3) adding the two new clusters to the cluster priority queue.