Three dimensional modeling and rendering of head hair

A non-transitory computer readable medium for three dimensional modeling and rendering of head hair, the non-transitory computer readable medium that stores instructions for:

• obtaining a three dimensional (3D) point cloud of head hair points of a person;
• determining head hair points related 3D directions indicative of 3D directions of candidate strands that pass through the head hair points;
• wherein the determining of the head points directions comprises:
• creating multiple two dimensional (2D) projections of the 3D point cloud;
• applying a direction finding process on each of the multiple 2D projections of the 3D point cloud to provide multiple head hair points 2D direction related estimations;
• and determining the head hair points 3D directions based on the multiple head hair points 2D direction estimations;
• grouping the head hair points into multiple strand groups, wherein the grouping is based on distances between the head hair points and the head hair points 3D directions;
• wherein each strand group is associated with strand spatial information;
• and
• generating, by a machine learning process, a representation of the head hair based on strand spatial information of the multiple strand groups and on strand shape information.

A method for three dimensional modeling and rendering of head hair, the method comprises:

• obtaining a three dimensional (3D) point cloud of head hair points of a person;
• determining head hair points related 3D directions indicative of 3D directions of candidate strands that pass through the head hair points;
• wherein the determining of the head points directions comprises:
• creating multiple two dimensional (2D) projections of the 3D point cloud;
• applying a direction finding process on each of the multiple 2D projections of the 3D point cloud to provide multiple head hair points 2D direction related estimations;
• and determining the head hair points 3D directions based on the multiple head hair points 2D direction estimations;
• grouping the head hair points into multiple strand groups, wherein the grouping is based on distances between the head hair points and the head hair points 3D directions;
• wherein each strand group is associated with strand spatial information;
• generating, by a machine learning process, head hair metadata regarding head hair based on strand spatial information of the multiple strand groups and on strand shape information;
• wherein the head hair metadata is renderable from any point of view.

A non-transitory computer readable medium for three dimensional modeling and rendering of head hair, the non-transitory computer readable medium that stores instructions for:

• obtaining a three dimensional (3D) point cloud of head hair points of a person;
• determining head hair points related 3D directions indicative of 3D directions of candidate strands that pass through the head hair points;
• wherein the determining of the head points directions comprises:
• creating multiple two dimensional (2D) projections of the 3D point cloud;
• applying a direction finding process on each of the multiple 2D projections of the 3D point cloud to provide multiple head hair points 2D direction related estimations;
• and determining the head hair points 3D directions based on the multiple head hair points 2D direction estimations;
• grouping the head hair points into multiple strand groups, wherein the grouping is based on distances between the head hair points and the head hair points 3D directions;
• wherein each strand group is associated with strand spatial information;
• and
• generating, by a machine learning process, head hair metadata regarding head hair based on strand spatial information of the multiple strand groups and on strand shape information;
• and wherein the head hair metadata is renderable from any point of view.

A method for three dimensional modeling and rendering of head hair, the method comprises:

• obtaining a machine learning process that is trained to generate a representation of a head hair from any point of view;
• determining by the machine learning process, head hair points related 3D directions indicative of 3D directions of candidate strands that pass through the head hair points;
• wherein the determining of the head points directions comprises:
• creating multiple two dimensional (2D) projections of the 3D point cloud;
• applying a direction finding process on each of the multiple 2D projections of the 3D point cloud to provide multiple head hair points 2D direction related estimations;
• and determining the head hair points 3D directions based on the multiple head hair points 2D direction estimations;
• receiving by the machine learning process, (a) strand spatial information of multiple strand groups that are formed from head hair points, and (b) strand shape information;
• generating, by the machine learning process, a representation of the head hair based on the strand spatial information of the multiple strand groups and on the strand shape information.

A non-transitory computer readable medium for three dimensional modeling and rendering of head hair, the non-transitory computer readable medium that stores instructions for:

• obtaining a machine learning process that is trained to generate a representation of a head hair from any point of view;
• determining by the machine learning process, head hair points related 3D directions indicative of 3D directions of candidate strands that pass through the head hair points;
• wherein the determining of the head points directions comprises:
• creating multiple two dimensional (2D) projections of the 3D point cloud;
• applying a direction finding process on each of the multiple 2D projections of the 3D point cloud to provide multiple head hair points 2D direction related estimations;
• and determining the head hair points 3D directions based on the multiple head hair points 2D direction estimations;
• receiving by the machine learning process, (a) strand spatial information of multiple strand groups that are formed from head hair points, and (b) strand shape information;
• generating, by the machine learning process, a representation of the head hair based on the strand spatial information of the multiple strand groups and on the strand shape information.