Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Niraj Bhujel"'
Autor:
Niraj Bhujel, Wei-Yun Yau
Publikováno v:
IEEE Robotics and Automation Letters. 8:3078-3085
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::592bc2ee64c2d7b8b0d55ac531546753
https://doi.org/10.1109/lra.2023.3262420
https://doi.org/10.1109/lra.2023.3262420
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fa119c9a377929b49bade9f44650614
https://doi.org/10.1109/iros51168.2021.9636641
https://doi.org/10.1109/iros51168.2021.9636641
Publikováno v:
IROS
Multi-human tracking in the crowded environment is a challenging problem due to occlusions, pose change, viewpoint variation and cluttered background. In this work, we propose a robust feature learning for tracking-by-detection methods based on secon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4684fb6e33074556664540fca93e9654
https://doi.org/10.1109/iros45743.2020.9341625
https://doi.org/10.1109/iros45743.2020.9341625
Publikováno v:
ICRAI
Deep learning is the current state-of-the-art technique for most machine learning and data analytics tasks. It has been applied to all aspects of human life. Traditional methods are not competitive for solving pedestrian trajectory prediction problem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::796a3314f2d1491c97666e066a3df1e8
https://doi.org/10.1145/3373724.3373729
https://doi.org/10.1145/3373724.3373729
Publikováno v:
2019 IEEE 5th International Conference on Mechatronics System and Robots (ICMSR).
Pedestrian motion are inherently multi-modal in nature influenced by presence of other human and physical objects in the environment. Traiectory prediction models need to address both human-human and human-space interaction issues. In this work, we l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::423e7cf68aff90780c532cb27a59da77
https://doi.org/10.1109/icmsr.2019.8835478
https://doi.org/10.1109/icmsr.2019.8835478