Anthropometry, Greek for human measurement, is a tool widely used across many scientific disciplines. Clinical nutrition applications include phenotyping subjects across the lifespan for assessing growth, body composition, response to treatments, and predicting health risks. The simple anthropometric tools such as flexible measuring tapes and calipers are now being supplanted by rapidly developing digital technology devices. These systems take many forms, but excitement today surrounds the introduction of relatively low cost three-dimensional optical imaging methods that can be used in research, clinical, and even home settings. This review examines this transformative technology, providing an overview of device operational details, early validation studies, and potential applications. Digital anthropometry is rapidly transforming dormant and static areas of clinical nutrition science with many new applications and research opportunities.

Digital anthropometry: a critical review.

This paper introduces a new shape matching algorithm for computing correspondences between 3D surfaces that have undergone (approximately) isometric deformations. The new approach makes two main contributions: First, the algorithm is, unlike previous work, robust to “topological noise” such as large holes or “false connections”, which is both observed frequently in real-world scanner data. Second, our algorithm samples the space of feasible solutions such that uncertainty in matching can be detected explicitly. We employ a novel randomized feature matching algorithm in order to find robust subsets of geodesics to verify isometric consistency. The paper shows shape matching results for real world and synthetic data sets that could not be handled using previous deformable matching algorithms.

Isometric Registration of Ambiguous and Partial Data

The problem of the restoration of broken artifacts, where large parts could be missing, is of high importance in archaeology. The typical manual restoration can become a tedious and error-prone process, which also does not scale well. In recent years, many methods have been proposed for assisting the process, most of which target specialized object types or operate under very strict constraints. We propose a digital shape restoration pipeline consisting of proven, robust methods for automatic fragment reassembly and shape completion of generic three-dimensional objects of arbitrary type. In this pipeline, first we introduce a novel unified approach for handling the reassembly of objects from heavily damaged fragments by exploiting both fracture surfaces and salient features on the intact sides of fragments, when available. Second, we propose an object completion procedure based on generalized symmetries and a complementary part extraction process that is suitable for driving the fabrication of missing geometry. We demonstrate the effectiveness of our approach using real-world fractured objects and software implemented as part of the European Union--funded PRESIOUS project, which is also available for download from the project site.

From Reassembly to Object Completion: A Complete Systems Pipeline

Automated anthropometric phenotyping with novel Kinect-based three-dimensional imaging method: comparison with a reference laser imaging system

Automated anthropometric phenotyping with novel Kinect-based three-dimensional imaging method: comparison with a reference laser imaging system.

http://jjcao.weebly.com/uploads/4/5/3/4/4534726/accepte-online-automatic_hole-filling_of_cad_models_with_feature-preserving1.pdf

Technical Section: Automatic hole-filling of CAD models with feature-preserving

Cultural Heritage: Symmetry and template guided completion of damaged skulls

We develop a geometric reassembly algorithm that composes a 3D model from its fragments. One important application of this work is skull completion and modeling in archeology and forensics. Our reassembly algorithm employs a scale-space representation of shape based on the heat kernel, which only depends on the intrinsic geometry of the surfaces. Partial matching can then be conducted effectively. The entire assembly pipeline has three steps: (1) fragment-template matching based on heat-kernel; (2) matching refinement based on RANSAC and assembly computation; (3) assembly refinement using least square transformation error (LSTE) of break-curves. The main contribution of this paper is presenting novel algorithms for the first two steps. Experimental results on scanned skull fragments demonstrate the efficacy and robustness of our algorithm.

/pdf/fragmented-skull-modeling-using-heat-kernels-2z7nygp6mk.pdf

Fragmented skull modeling using heat kernels

We present a skull assembly and completion framework based on shape matching. In order to assemble fragmented skulls, we need to compute rigid transformations from these fragments to their assembled geometry. We develop a reliable assembly pipeline where each fragment is matched and transformed to be aligned with the template. In order to further complete the assembled skull with several damaged regions, we use the template to repair damaged regions on the assembled skull. The entire pipeline has been conducted on several real skull models and demonstrated great robustness and effectiveness.

Skull Assembly and Completion Using Template-Based Surface Matching

We develop a 3D mesh completion system for archaeological data. Topology inconsistency (such as local self-intersections) and holes on triangle meshes are detected and repaired via a dynamic programming paradigm. We demonstrate the effectiveness of our methodology on several datasets. The developed system is used for archaeological and forensic data completion. It serves as an important preprocessing step for many subsequent data analysis/processing tasks of forensic anthropologists.

Hole filling using dynamic programming for archaeological data completion

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Cultural Heritage: Symmetry and template guided completion of damaged skulls

Fragmented skull modeling using heat kernels

Skull Assembly and Completion Using Template-Based Surface Matching

Hole filling using dynamic programming for archaeological data completion