Virtual try-on and product personalization have become increasingly important
in modern online shopping, highlighting the need for accurate body measurement
estimation. Although previous research has advanced in estimating 3D body
shapes from RGB images, the task is inherently ambiguous as the observed scale
of human subjects in the images depends on two unknown factors: capture
distance and body dimensions. This ambiguity is particularly pronounced in
partial-view scenarios. To address this challenge, we propose a modular and
simple height normalization solution. This solution relocates the subject
skeleton to the desired position, thereby normalizing the scale and
disentangling the relationship between the two variables. Our experimental
results demonstrate that integrating this technique into state-of-the-art human
mesh reconstruction models significantly enhances partial body measurement
estimation. Additionally, we illustrate the applicability of this approach to
multi-view settings, showcasing its versatility.

提出了一种模块化和简单的高度标准化方案，通过将主体骨架重定位到所需位置，标准化比例并解脱两个变量之间的关系，显著提高了部分身体测量估计。此方法在多视图设置下也具有适用性。