all AI news
You Are How You Walk: Uncooperative MoCap Gait Identification for Video Surveillance with Incomplete and Noisy Data. (arXiv:1706.09443v3 [cs.CV] UPDATED)
Web: http://arxiv.org/abs/1706.09443
June 16, 2022, 1:13 a.m. | Michal Balazia, Petr Sojka
cs.CV updates on arXiv.org arxiv.org
This work offers a design of a video surveillance system based on a soft
biometric -- gait identification from MoCap data. The main focus is on two
substantial issues of the video surveillance scenario: (1) the walkers do not
cooperate in providing learning data to establish their identities and (2) the
data are often noisy or incomplete. We show that only a few examples of human
gait cycles are required to learn a projection of raw MoCap data onto a …
More from arxiv.org / cs.CV updates on arXiv.org
Latest AI/ML/Big Data Jobs
Machine Learning Researcher - Saalfeld Lab
@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia
Project Director, Machine Learning in US Health
@ ideas42.org | Remote, US
Data Science Intern
@ NannyML | Remote
Machine Learning Engineer NLP/Speech
@ Play.ht | Remote
Research Scientist, 3D Reconstruction
@ Yembo | Remote, US
Clinical Assistant or Associate Professor of Management Science and Systems
@ University at Buffalo | Buffalo, NY