Print Email Facebook Twitter Hand-tremor frequency estimation in videos Title Hand-tremor frequency estimation in videos Author Pintea, S. (TU Delft Pattern Recognition and Bioinformatics) Zheng, Jian (Student TU Delft) Li, Xilin (Student TU Delft) Bank, Paulina J.M. (Leiden University Medical Center) van Hilten, Jacobus J. (Leiden University Medical Center) van Gemert, J.C. (TU Delft Pattern Recognition and Bioinformatics) Contributor Leal-Taixé, Laura (editor) Roth, Stefan (editor) Date 2019 Abstract We focus on the problem of estimating human hand-tremor frequency from input RGB video data. Estimating tremors from video is important for non-invasive monitoring, analyzing and diagnosing patients suffering from motor-disorders such as Parkinson’s disease. We consider two approaches for hand-tremor frequency estimation: (a) a Lagrangian approach where we detect the hand at every frame in the video, and estimate the tremor frequency along the trajectory; and (b) an Eulerian approach where we first localize the hand, we subsequently remove the large motion along the movement trajectory of the hand, and we use the video information over time encoded as intensity values or phase information to estimate the tremor frequency. We estimate hand tremors on a new human tremor dataset, TIM-Tremor, containing static tasks as well as a multitude of more dynamic tasks, involving larger motion of the hands. The dataset has 55 tremor patient recordings together with: associated ground truth accelerometer data from the most affected hand, RGB video data, and aligned depth data. Subject Eulerian hand tremorsHuman tremor datasetPhase-based tremor frequency detectionVideo hand-tremor analysis To reference this document use: http://resolver.tudelft.nl/uuid:e790615d-3a7f-4f16-8864-c811e1100eaf DOI https://doi.org/10.1007/978-3-030-11024-6_14 Publisher Springer, Cham ISBN 978-303011023-9 Source Computer Vision: ECCV 2018 Workshops, Proceedings (Part VI) Event 15th European Conference on Computer Vision, ECCV 2018, 2018-09-08 → 2018-09-14, Munich, Germany Series Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 0302-9743, 11134 LNCS Part of collection Institutional Repository Document type conference paper Rights © 2019 S. Pintea, Jian Zheng, Xilin Li, Paulina J.M. Bank, Jacobus J. van Hilten, J.C. van Gemert Files PDF Pintea_Hand_tremor_freque ... _paper.pdf 1.34 MB Close viewer /islandora/object/uuid:e790615d-3a7f-4f16-8864-c811e1100eaf/datastream/OBJ/view