A 3-Dimensional Object Recognition Method Using SHOT and Relationship of Distances and Angles in Feature Points

2017 ◽  
Vol 7 (4) ◽  
pp. 149-155
Author(s):  
Hiroyuki Kudo ◽  
Keyword(s):  
Object Recognition ◽  
Feature Points ◽  
Recognition Method ◽  
3 Dimensional ◽  
Dimensional Object ◽  
Relationship Of

A 3-Dimensional Object Recognition Method Using Relationship of Distances and Angles in Feature Points

2017 ◽  
Vol 17 (04) ◽  
pp. 1750019 ◽  
Author(s):  
Seiichi Maehara ◽  
Kazuo Ikeshiro ◽  
Hiroki Imamura
Keyword(s):  
Object Recognition ◽  
Recognition Task ◽  
Feature Points ◽  
Recognition Method ◽  
3 Dimensional ◽  
Fast Recognition ◽  
Dimensional Object ◽  
Relationship Of ◽  
Human Support ◽  
Spin Image

In recent years, human support robots have been receiving attention. Especially, object recognition task is important in case that people request the robots to transport and rearrange an object. We consider that there are four necessary properties to recognize in domestic environment as follows. (1) Robustness against occlusion. (2) Fast recognition. (3) Pose estimation with high accuracy. (4) Coping with erroneous correspondences. As conventional object recognition methods using 3-dimensional information, there are model-based recognition methods such as the SHOT and the Spin Image. The SHOT and the Spin Image do not satisfy all four properties for the robots. Therefore, to satisfy the four properties of recognition, we propose a 3-dimensional object recognition method by using relationship of distances and angles in feature points. As per our approach, the proposed method achieves to solve problems of conventional methods by using not only the feature points but also relationship between feature points. To achieve this purpose, firstly, the proposed method uses a curvature as a feature in a local region. Secondly, the proposed method uses points having high curvature as feature points. Finally, the proposed method generates a list by listing relationship of distances and angles between feature points and matches lists.

Symbolic Surface Descriptors For 3-Dimensional Object Recognition

1987 ◽  
Author(s):  
Ramesh Jain ◽  
Thawach Sripradisvarakul ◽  
Nancy O'Brien
Keyword(s):  
Object Recognition ◽  
3 Dimensional ◽  
Dimensional Object

scholarly journals A Robot Object Recognition Method Based on Scene Text Reading in Home Environments

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1919
Author(s):  
Shuhua Liu ◽  
Huixin Xu ◽  
Qi Li ◽  
Fei Zhang ◽  
Kun Hou
Keyword(s):  
Object Recognition ◽  
Recognition Accuracy ◽  
Multiple Objects ◽  
Recognition Method ◽  
Home Environments ◽  
Complex Scenes ◽  
Scene Text ◽  
Text Reading ◽  
Text Images ◽  
Chinese And English

With the aim to solve issues of robot object recognition in complex scenes, this paper proposes an object recognition method based on scene text reading. The proposed method simulates human-like behavior and accurately identifies objects with texts through careful reading. First, deep learning models with high accuracy are adopted to detect and recognize text in multi-view. Second, datasets including 102,000 Chinese and English scene text images and their inverse are generated. The F-measure of text detection is improved by 0.4% and the recognition accuracy is improved by 1.26% because the model is trained by these two datasets. Finally, a robot object recognition method is proposed based on the scene text reading. The robot detects and recognizes texts in the image and then stores the recognition results in a text file. When the user gives the robot a fetching instruction, the robot searches for corresponding keywords from the text files and achieves the confidence of multiple objects in the scene image. Then, the object with the maximum confidence is selected as the target. The results show that the robot can accurately distinguish objects with arbitrary shape and category, and it can effectively solve the problem of object recognition in home environments.

A Timely Object Recognition Method for Construction using the Mask R-CNN Architecture

2021 ◽  
Author(s):  
Dena Shamsollahi ◽  
Osama Moselhi ◽  
Khashayar Khorasani
Keyword(s):  
Object Recognition ◽  
Recognition Method
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