3D Reconstruction of Video Sign Language Dictionaries

Riazantsev, Roman

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dc.contributor.author	Riazantsev, Roman
dc.date.accessioned	2020-01-28T12:53:29Z
dc.date.available	2020-01-28T12:53:29Z
dc.date.issued	2020
dc.identifier.citation	Riazantsev, Roman. 3D Reconstruction of Video Sign Language Dictionaries : Master Thesis : manuscript rights / Maksym Davydov ; Supervisor Dr. Rostyslav Hryniv ; Ukrainian Catholic University, Department of Computer Sciences. – Lviv : [s.n.], 2020. – 34 p. : ill.	uk
dc.identifier.uri	http://er.ucu.edu.ua/handle/1/1902
dc.language.iso	en	uk
dc.subject	MANO model	uk
dc.subject	3D reconstruction	uk
dc.subject	2D key point detection	uk
dc.title	3D Reconstruction of Video Sign Language Dictionaries	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	Today virtual and augmented reality applications become more and more popular. Such a trend creates a demand for 3D processing algorithms which may be applied to many areas. This work is focused on sign language video sequences. There are a lot of prerecorded photo and video dictionaries that can be transformed into 3D and uniﬁed in one place. We research nuances of hand pose video sequence analysis as well as the inﬂuence of results reﬁnement for 2D and 3D keypoint detection. Besides that, we designed a solution for the parametrization of hand shape and engineered system for 3D hand pose reconstruction. Model show good results on train data but lack generalization. Retraining on multiple datasets and usage of various data augmentation techniques will improve performance.	uk