UCSY's Research Repository

Real-Time Human Motion Detection, Tracking and Activity Recognition with Skeletal Model

Show simple item record

dc.contributor.author Win, Sandar
dc.contributor.author Thein, Thin Lai Lai
dc.date.accessioned 2021-01-31T13:15:00Z
dc.date.available 2021-01-31T13:15:00Z
dc.date.issued 2020-02-28
dc.identifier.uri https://onlineresource.ucsy.edu.mm/handle/123456789/2574
dc.description.abstract Human activity recognition with 3Dskeletal model has been attracted in a lot of application area. Representations of human based on 3D perception have been occurred prevalent problems in activity recognition. In recent work with RGB-Depth cameras, expensive wearable sensors and illuminator array have been used to construct the 3D human skeleton model in recognition system. But these systems have been defined specific lightening condition, limited range. and great constraint in outdoor applications. To overcome this restriction, the proposed system is considered on the real-time video sequences of the human movement to understand human behavior in indoor and outdoor environment. The proposed method is constructed human detection and motion tracking by using framewise displacement and recognition is based on skeletal model with deep learning framework. The result is to become an efficient detection, tracking and recognition system for real-time human motion. The performance and accuracy of the system is analyzed with the various videos to show the results. en_US
dc.language.iso en en_US
dc.publisher Proceedings of the Eighteenth International Conference On Computer Applications (ICCA 2020) en_US
dc.subject human recognition en_US
dc.subject skeletal model en_US
dc.subject deep learning en_US
dc.title Real-Time Human Motion Detection, Tracking and Activity Recognition with Skeletal Model en_US
dc.type Article en_US

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Repository


My Account