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- W2917629371 abstract "Abstract Archaeozoology or zooarchaeology is the scientific field that aims to rebuild natural and cultural relations between human and animals. To reach that objective, archaeozoologists study faunal remains, such as bones. In this regard, a 3D representation is put into place. This would allow a better understanding of the initial spatial positions of the animals in the pits, and would make it possible to examine in a more rigorous manner the explanatory hypotheses by manipulating the 3D view of the pit and bones. This manipulation invokes the use of computer vision techniques, including 3D object recognition methods. In this work we present a novel approach to recognize 3D bones in occluded and cluttered scenes inspiring from a stat of the art method called spin images. We combine this method with saliency concept to improve the the robustness to occlusions and clutters significantly and also to decrease the complexity of the algorithm." @default.
- W2917629371 created "2019-03-02" @default.
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- W2917629371 date "2019-01-01" @default.
- W2917629371 modified "2023-09-27" @default.
- W2917629371 title "Salient Spin Images : an application to archaeozoology for bones recognition" @default.
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- W2917629371 doi "https://doi.org/10.1016/j.procs.2019.01.032" @default.
- W2917629371 hasPublicationYear "2019" @default.
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