iBODY: Human body shape reconstruction by using multiple depth cameras

Abstract: Diverse 3D body shapes of the human body can be collected and statistically analyzed to construct a collection of representative human body shapes. Such a digital human model can be used to realize a design that reasonably takes into account the diversity of the human body, so-called human-centered design, on a computer.A device that measures the three-dimensional body shape of the human body is generally called a 3D body scanner. Although body scanners using laser beams are extremely accurate, they are very expensive and require the subject to keep static for a long time. Photogrammetry, a method that reconstructs body shapes from color images obtained by placing dozens or hundreds of cameras around a subject, can generate dense meshes with realistic textures of the subject's body shape, but the equipment is large and expensive, and the accuracy is difficult to verify. On the other hand, a body scanner using depth cameras can acquire a wide range of high-density point clouds in a short time and requires a small number of cameras, making it relatively inexpensive to build a scanner.This paper describes a new 3D body shape measurement method using multiple depth cameras. The task of identifying the position and orientation of each depth camera in the 3D world coordinate system is generally referred to as global calibration, and conventionally requires that a default checkerboard can be captured from each camera. In this paper, we propose a new global calibration method using a real object of known shape. Only a single object is placed for the measurement area, and calibration is possible as long as any part of the surface shape of this object can be captured from each camera.Furthermore, this paper describes a method to construct a homologous mesh using the obtained high-density point cloud of the human body surface. By constructing the mesh in which the configuration of vertices and faces is invariant regardless of the body shape, dimensional measurements and other analyses are facilitated.

Keywords: digital human, human-centered design, body scanner, human modeling

DOI: 10.54941/ahfe1004247

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