Active Object Recognition via Monte Carlo Tree Search
Lauri, Mikko; Atanasov, Nikolay; Pappas, George; Ritala, Risto (2015-05-30)
Lauri, Mikko
Atanasov, Nikolay
Pappas, George
Ritala, Risto
30.05.2015
ICRA 2015 Workshop: Beyond Geometric Constraints
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201706151600
https://urn.fi/URN:NBN:fi:tty-201706151600
Tiivistelmä
This paper considers object recognition with a camera, whose viewpoint can be controlled in order to improve the recognition results. The goal is to choose a multi-view camera trajectory in order to minimize the probability of having misclassified objects and incorrect orientation estimates. Instead of using offline dynamic programming, the resulting stochastic optimal control problem is addressed via an online Monte Carlo tree search algorithm, which can handle various constraints and provides exceptional performance in large state spaces. A key insight is to use an active hypothesis testing policy to select camera viewpoints during the rollout stage of the tree search.
Kokoelmat
- TUNICRIS-julkaisut [19011]