Multiview Object and View Sequence Recognition using Hidden Markov Models

被引：0
|
作者：
Nunez, Lorena [1 ]
Negrete, Marco [1 ]
Savage, Jesus [1 ]
Contreras, Luis [2 ]
Moctezuma, Miguel [3 ]
机构：
[1] Natl Autonomous Univ Mexico UNAM, Sch Engn, Biorobot Lab, Cdmx 04510, Mexico
[2] Tamagawa Univ, Adv Intelligence & Robot Res Ctr, Machida, Tokyo, Japan
[3] Natl Autonomous Univ Mexico UNAM, Sch Engn, Cdmx 04510, Mexico
来源：
2022 IEEE 18TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE) | 2022年
关键词：
D O I：
10.1109/CASE49997.2022.9926680
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This work presents a method for multiview object recognition and the estimation of the sequence of object views. The main feature of the method is to be lightweighted, which can be crucial for future sensor technology. This goal is achieved with a hidden Markov model of the 3D object from information of a sequence of 2D images. COIL 100 dataset were used for testing the method. The tests included images affected by rotation as well as Gaussian noise. Consistent results were obtained using relatively few shots of each class for the training process.
引用
收藏
页码：589 / 594
页数：6
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