VNU-UET Repository: No conditions. Results ordered -Date Deposited. 2024-03-28T20:15:51ZEPrintshttp://eprints.uet.vnu.edu.vn/images/sitelogo.pnghttps://eprints.uet.vnu.edu.vn/eprints/2020-12-07T14:07:31Z2020-12-21T09:33:05Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/4155This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/41552020-12-07T14:07:31ZPCA-Based Robust Motion Data RecoveryHuman motion tracking is a prevalent technique in many fields. A common difficulty encountered in motion tracking is the corrupted data is caused by detachment of markers in 3D motion data or occlusion in 2D tracking data. Most methods for missing markers problem may quickly become ineffective when gaps exist in the trajectories of multiple markers for an extended duration. In this paper, we propose the principal component eigenspace based gap filling methods that leverage a training sample set for estimation. The proposed method is especially beneficial in the scenario of motion data with less predictable or repeated movement patterns, and that of even missing entire frames within an interval of a sequence. To highlight algorithm robustness, we perform algorithms on twenty test samples for comparison. The experimental results show that our methods are numerical stable and fast to work.Zhuorong LiHongchuan YuHai Dang KieuTung Long VuongJian Jun Zhang2019-12-09T02:49:20Z2019-12-10T02:46:07Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3742This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/37422019-12-09T02:49:20ZSharing Experience in Multitask Reinforcement LearningTung Long VuongDo Van Nguyenngdovan@gmail.comTai Long NguyenCong Minh BuiHai Dang KieuViet Cuong TaQuoc Long Trantqlong@vnu.edu.vnThanh Ha Leltha@vnu.edu.vn2018-12-17T02:54:01Z2018-12-17T02:54:01Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3294This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/32942018-12-17T02:54:01ZVision Memory for Target Object Navigation using Deep Reinforcement Learning: An Emperical StudyDo Van Nguyenngdovan@gmail.comTung Long VuongHai Dang KieuLinh PhamThanh Ha Leltha@vnu.edu.vn