JOURNAL ARTICLE

3D Object Detection from Point Cloud Based on Deep Learning

Ning Hao

Year: 2022 Journal:   Wireless Communications and Mobile Computing Vol: 2022 (1)   Publisher: Wiley

Abstract

In order to study the modern 3D object detection algorithm based on deep learning, this paper studies the point‐based 3D object detection algorithm, that is, a 3D object detection algorithm that uses multilayer perceptron to extract point features. This paper proposes a method based on point RCNN. A three‐stage 3D object detection algorithm improves the accuracy of the algorithm by fusing image information. The algorithm in this paper integrates the information and image information of the three stages well, which improves the information utilization of the whole algorithm. Compared with the traditional 3D target detection algorithm, the structure of the algorithm in this paper is more compact, which effectively improves the utilization of information.

Keywords:
Computer science Artificial intelligence Object (grammar) Point cloud Object detection Point (geometry) Algorithm Deep learning Pattern recognition (psychology) Computer vision Mathematics

Metrics

8
Cited By
2.03
FWCI (Field Weighted Citation Impact)
27
Refs
0.75
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

3D Shape Modeling and Analysis
Physical Sciences →  Engineering →  Computational Mechanics
Remote Sensing and LiDAR Applications
Physical Sciences →  Environmental Science →  Environmental Engineering
3D Surveying and Cultural Heritage
Physical Sciences →  Earth and Planetary Sciences →  Geology
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