Active Object Recognition Based on Prior Feature Distribution Table | |
Sun HB(孙海波)1,2,3; Zhu F(朱枫)2,3![]() ![]() ![]() | |
Department | 光电信息技术研究室 |
Conference Name | 2020 3rd International Conference on Unmanned Systems (ICUS) |
Conference Date | November 27-28, 2020 |
Conference Place | Harbin, China |
Source Publication | 2020 3rd International Conference on Unmanned Systems (ICUS) |
Publisher | IEEE |
Publication Place | New York |
2020 | |
Pages | 1012-1017 |
Indexed By | EI |
EI Accession number | 20210209751087 |
Contribution Rank | 1 |
ISBN | 978-1-7281-8025-0 |
Keyword | Active object recognition Prior feature distribution table Feature decision tree Next best viewpoint |
Abstract | In this paper, an active object recognition (AOR) method based on a prior feature distribution table (PFDT) is proposed. According to the distribution information of predetermined features on each object in the model base, the prior feature distribution table is created. Taking it as input, a feature decision tree (FDT) is constructed for object recognition and viewpoint planning (VP). To determine the next best viewpoint, we transform it into an optimization problem that is solved with the tree dynamic programming algorithm. Experiments show that the proposed method can achieve the object recognition task with the minimum average number of viewpoints. |
Language | 英语 |
Document Type | 会议论文 |
Identifier | http://ir.sia.cn/handle/173321/27999 |
Collection | 光电信息技术研究室 |
Corresponding Author | Sun HB(孙海波) |
Affiliation | 1.Northeastern University, Shenyang, China 2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China 4.University of Chinese Academy of Sciences, Shenyang, China |
Recommended Citation GB/T 7714 | Sun HB,Zhu F,Hao YM,et al. Active Object Recognition Based on Prior Feature Distribution Table[C]. New York:IEEE,2020:1012-1017. |
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Active Object Recogn(303KB) | 会议论文 | 开放获取 | CC BY-NC-SA | View Application Full Text |
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