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Human grasping database for activities of daily living with depth, color and kinematic data streams

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dc.contributor.author Saudabayev, Artur
dc.contributor.author Rysbek, Zhanibek
dc.contributor.author Khassenova, Raykhan
dc.contributor.author Varol, Huseyin Atakan
dc.date.accessioned 2019-09-03T04:23:07Z
dc.date.available 2019-09-03T04:23:07Z
dc.date.issued 2018-05-29
dc.identifier.citation Saudabayev, A., Rysbek, Z., Khassenova, R., & Varol, H. A. (2018). Human grasping database for activities of daily living with depth, color and kinematic data streams. Scientific data, 5, 180101. en_US
dc.identifier.uri https://www.nature.com/articles/sdata2018101
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/4209
dc.description.abstract This paper presents a grasping database collected from multiple human subjects for activities of daily living in unstructured environments. The main strength of this database is the use of three different sensing modalities: color images from a head-mounted action camera, distance data from a depth sensor on the dominant arm and upper body kinematic data acquired from an inertial motion capture suit. 3826 grasps were identified in the data collected during 9-hours of experiments. The grasps were grouped according to a hierarchical taxonomy into 35 different grasp types. The database contains information related to each grasp and associated sensor data acquired from the three sensor modalities. We also provide our data annotation software written in Matlab as an open-source tool. The size of the database is 172 GB. We believe this database can be used as a stepping stone to develop big data and machine learning techniques for grasping and manipulation with potential applications in rehabilitation robotics and intelligent automation. en_US
dc.language.iso en en_US
dc.publisher Nazarbayev University, School of Engineering and Digital Sciences en_US
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject digital camera en_US
dc.subject Range Imaging en_US
dc.subject motion sensors en_US
dc.subject observation design en_US
dc.title Human grasping database for activities of daily living with depth, color and kinematic data streams en_US
dc.type Article en_US
workflow.import.source science


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