UID:
edoccha_9959842749302883
Format:
1 online resource (228 pages) :
,
illustrations.
Series Statement:
Karlsruher Schriften zur Anthropomatik
Content:
This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together.
Note:
English.
Additional Edition:
ISBN 1000122541
Language:
English
DOI:
10.5445/KSP/1000122541
