# Measurement-Driven Synthesis of Female Digital Mannequin Using Convex Sub-Volumes
## 2 Literature Review
### Conclusions of Literature Review  
The main conclusions of the literature review are presented in this section with a summary exhibited in Table 1. This table exhibits a comparison between the advantages/disadvantages of previous schemes and of the approach presented in this manuscript. Such a comparison seeks to support the contributions made by the proposed approach.  
In the current literature, the human body is modeled as non-convex meshes, with exceptions found in some components of the models produced by anatomy-based methods. These non-convex meshes are computationally expensive to process for pose variation and collision detection simulations (e.g., garment-fitting), among other implementations. In addition, example-based approaches present particular disadvantages in (1) requiring expensive hardware, (2) storage of large amounts of data, (3) usage of smoothing and surface-fitting algorithms, and (4) expensive extraction of features and identification of feature-parameter relations. It is also noted that anatomy-based approaches do not parameterize the general shape and size of the model. In contrast, they requires manual intervention for modeling a particular phenotype.  
To overcome these limitations, this manuscript proposes a parametric modeling scheme based on convex volumes. The scheme synthesizes sets of convex volumes (man-nequins) from sets of tailor measurements and a small set of manually created Reference Mannequins (\(RM\)). Furthermore, the synthesized models satisfy the input measurements. This approach presents the following **contributions**: (a) avoids the need for hardware and the storage of large amounts of data, (b) enables pose variation through kinematic chains without re-computing surfaces, (c) simple and straightforward parameterization with minimal tuning, and (d) the synthesized mannequins are ready-to-simulate and do  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Approach** & **Refs.** & **Advantages** & **Disadvantages** \\ \hline \multirow{6}{*}{Non-Convex Example-Based Synthesis Approach} & & & (1) A non-convex model is produced. (2) Needs further processing steps to generate a ready-to-simulate model. (3) Expensive algorithms for deformation and surface-fitting. (4) Pose limitation or need to recompute/deform surfaces for pose changes. (5) \\  & & & (1) A non-convex model is produced. (2) Needs further processing steps to generate a ready-to-simulate model. (3) Expensive algorithms for deformation and surface-fitting. (4) Pose limitation or need to recompute/deform surfaces for pose changes. (5) \\  & & & Dependent on hardware and/or a large database of examples. \\ \hline Non-Convex Anatomy Based Approach: Bone, Muscle, Tissue Construction & [33; 34] & (1) Anatomic fidelity of the model. (2) High kinematic fidelity can be achieved. & (1) A non-convex model is produced. (2) High computation expenses. (3) Construction of unnecessary internal elements to reproduce external surfaces. (4) Phenotype limitation. \\ \hline \multirow{6}{*}{Synthesis Based on Convex Volumes} & & (1) Low computational costs. (2) No intermediate steps for the preparation of the model for physics simulation. (3) Simple and straightforward parameterization with minimal tuning. (4) Reduced storage of data. (5) No need of re-computations of surfaces to change poses. & (1) Low model resolution, leaving out intricate details of the body. (2) Model surface does not have \(C^{1}\) surface continuity. \\  & & & (4) Low model resolution, leaving out intricate details of the body. (2) Model surface does not have \(C^{1}\) surface continuity. \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of previous approaches found in the literature plus our contribution.  
not need further processing. In conclusion, to the best of our knowledge, no other approach based on convex volumes is found in the literature. Hence, our approach proves novel.