Abstract
In this paper a novel framework is presented for interactive feature-based retrieval and visualization of human statues, using depth sensors for mobile devices. A skeletal model is fitted to the depth image of a statue or human body in general and is used as a feature vector that captures the pose variations in a given collection of skeleton data. A scale-and twist-invariant distance function is defined in the feature space and is employed in a topology-preserving low-dimensional lattice mapping framework. The user can interact with this self-organizing map by submitting queries in the form of a skeleton from a statue or a human body. The proposed methods are demonstrated in a real dataset of 3D digitized Graeco-Roman statues from Palazzo Altemps.
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CITATION STYLE
Barmpoutis, A., Bozia, E., & Fortuna, D. (2015). Interactive 3D digitization, retrieval, and analysis of ancient sculptures, using infrared depth sensors for mobile devices. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9178, pp. 3–11). Springer Verlag. https://doi.org/10.1007/978-3-319-20687-5_1
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