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Figure from:Interactive Virtual Hair Salon

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Figure |. Hairstyle interactively created with our system. accelerate dynamics computation and enable adaptive

Figure 1 |. Hairstyle interactively created with our system. accelerate dynamics computation and enable adaptive

Related Figures (8)

Figure 2. User interface: PHANToM provides 3D user input anc 2D menu buttons are labeled with icons to show applications.
Figure 2. User interface: PHANToM provides 3D user input anc 2D menu buttons are labeled with icons to show applications.
Figure 3. Level-of-detail (LOD) representations for modeling hair. (dq) Hair strip, (b) hair cluster, (c) hair strand, and (d) the dual- skeleton setup for simulating hair.
Figure 3. Level-of-detail (LOD) representations for modeling hair. (dq) Hair strip, (b) hair cluster, (c) hair strand, and (d) the dual- skeleton setup for simulating hair.
Figure 4. (a) All of the grid cells that contain hair geometry. (b) Highlights the cells that will be affected by the current application (applying water). (c) Water is applied to some hair, grid allows us to localize each application. action will have an effect. This area is defined as a trian- gle for the cutting tool and a cone for the remaining tools. The cone of influence is defined by the applica- tion’s position, orientation (or direction pointed), ength (how far it can reach), and cutoff angle (deter- mining its radius along its length). These properties de- fine the cone’s position in the grid. Inserting the cone becomes similar to inserting an LSS, but the offset be- comes a variable of distance along the core line (an SSV has a constant offset along its core shape). The triangle or cutting is defined by the space between the open blades of a pair of scissors.
Figure 4. (a) All of the grid cells that contain hair geometry. (b) Highlights the cells that will be affected by the current application (applying water). (c) Water is applied to some hair, grid allows us to localize each application. action will have an effect. This area is defined as a trian- gle for the cutting tool and a cone for the remaining tools. The cone of influence is defined by the applica- tion’s position, orientation (or direction pointed), ength (how far it can reach), and cutoff angle (deter- mining its radius along its length). These properties de- fine the cone’s position in the grid. Inserting the cone becomes similar to inserting an LSS, but the offset be- comes a variable of distance along the core line (an SSV has a constant offset along its core shape). The triangle or cutting is defined by the space between the open blades of a pair of scissors.
Figure 5. (a) Open blades of scissors define cutting triangle. (b) and (c) Top skeleton remains attached to scalp, bottom skeleto falls away after cut.
Figure 5. (a) Open blades of scissors define cutting triangle. (b) and (c) Top skeleton remains attached to scalp, bottom skeleto falls away after cut.
Figure 6. Example of haircutting, far right shows final style. the mass points of the global skeleton become heavier with the mass of the water. The overall motion of the hair is limited due to the extra weight and if the hair is curly, the global-skeleton will stretch under the extra weight and the curls will lengthen as expected. The vol- ume of the hair in the areas where water is applied is decreased by constricting the radius of the current hair representation (strand grouping, cluster, or strip); these hair segments are then rendered to show the wet ap- pearance (see Figure 6).
Figure 6. Example of haircutting, far right shows final style. the mass points of the global skeleton become heavier with the mass of the water. The overall motion of the hair is limited due to the extra weight and if the hair is curly, the global-skeleton will stretch under the extra weight and the curls will lengthen as expected. The vol- ume of the hair in the areas where water is applied is decreased by constricting the radius of the current hair representation (strand grouping, cluster, or strip); these hair segments are then rendered to show the wet ap- pearance (see Figure 6).
Figure 7. (a) User grabs and pulls a section of hair. (b) User releases grip and hair falls back into place. lected at a local point along the strands. In the simula- tion, the user presses the stylus button and the control points that fall within the cone of influence are decided. Among these selected control points, only one control point per dual skeleton is permitted to be grabbed; this rule correlates to the localized grabbing of a hair cluster when styling hair. If multiple control points of a single dual skeleton fall within the cone, the point that comes closest to the cone’s center will be chosen.
Figure 7. (a) User grabs and pulls a section of hair. (b) User releases grip and hair falls back into place. lected at a local point along the strands. In the simula- tion, the user presses the stylus button and the control points that fall within the cone of influence are decided. Among these selected control points, only one control point per dual skeleton is permitted to be grabbed; this rule correlates to the localized grabbing of a hair cluster when styling hair. If multiple control points of a single dual skeleton fall within the cone, the point that comes closest to the cone’s center will be chosen.
Figure 8. Comparison between real (top) and virtual use of common hair salon activities (from left to right). (1) Normal dry hair, (2) applying water, (3) some wet, some dry hair, (4) blow-drying hair
Figure 8. Comparison between real (top) and virtual use of common hair salon activities (from left to right). (1) Normal dry hair, (2) applying water, (3) some wet, some dry hair, (4) blow-drying hair
Figure 9. Simulation performance comparison. Shows the factor of speed-up for LODs with simulation localization and LODs over wisps alone. Here, the average runtime of the wisps is used as the baseline for comparison (value of | on this chart). Over the course of this simulation, the camera remained at a consistent distance from the figure and the viewer primarily faced the back of the avatar—causing distance and occlusion tests to have a small overall impact on the LOD choice. Note that the LODs with simulation localization outperforms both wisps and LODs alone, though the simulation varies over time as the user employs different applications. Figure 9. Simulation performance comparison. Shows the factor of
Figure 9. Simulation performance comparison. Shows the factor of speed-up for LODs with simulation localization and LODs over wisps alone. Here, the average runtime of the wisps is used as the baseline for comparison (value of | on this chart). Over the course of this simulation, the camera remained at a consistent distance from the figure and the viewer primarily faced the back of the avatar—causing distance and occlusion tests to have a small overall impact on the LOD choice. Note that the LODs with simulation localization outperforms both wisps and LODs alone, though the simulation varies over time as the user employs different applications. Figure 9. Simulation performance comparison. Shows the factor of