Attentive Rotation Invariant Convolution for Point Cloud-based Large Scale Place Recognition

08/29/2021
by   Zhaoxin Fan, et al.
1

Autonomous Driving and Simultaneous Localization and Mapping(SLAM) are becoming increasingly important in real world, where point cloud-based large scale place recognition is the spike of them. Previous place recognition methods have achieved acceptable performances by regarding the task as a point cloud retrieval problem. However, all of them are suffered from a common defect: they can't handle the situation when the point clouds are rotated, which is common, e.g, when viewpoints or motorcycle types are changed. To tackle this issue, we propose an Attentive Rotation Invariant Convolution (ARIConv) in this paper. The ARIConv adopts three kind of Rotation Invariant Features (RIFs): Spherical Signals (SS), Individual-Local Rotation Invariant Features (ILRIF) and Group-Local Rotation Invariant features (GLRIF) in its structure to learn rotation invariant convolutional kernels, which are robust for learning rotation invariant point cloud features. What's more, to highlight pivotal RIFs, we inject an attentive module in ARIConv to give different RIFs different importance when learning kernels. Finally, utilizing ARIConv, we build a DenseNet-like network architecture to learn rotation-insensitive global descriptors used for retrieving. We experimentally demonstrate that our model can achieve state-of-the-art performance on large scale place recognition task when the point cloud scans are rotated and can achieve comparable results with most of existing methods on the original non-rotated datasets.

READ FULL TEXT

page 1

page 2

page 10

research
02/26/2022

RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds Deep Learning

3D point clouds deep learning is a promising field of research that allo...
research
08/24/2023

VNI-Net: Vector Neurons-based Rotation-Invariant Descriptor for LiDAR Place Recognition

LiDAR-based place recognition plays a crucial role in Simultaneous Local...
research
10/23/2018

Point-cloud-based place recognition using CNN feature extraction

This paper proposes a novel point-cloud-based place recognition system t...
research
05/01/2021

SVT-Net: A Super Light-Weight Network for Large Scale Place Recognition using Sparse Voxel Transformers

Point cloud-based large scale place recognition is fundamental for many ...
research
03/25/2021

Equivariant Point Network for 3D Point Cloud Analysis

Features that are equivariant to a larger group of symmetries have been ...
research
11/01/2019

Rotation Invariant Point Cloud Classification: Where Local Geometry Meets Global Topology

Point cloud analysis is a basic task in 3D computer vision, which attrac...
research
09/23/2022

GIDP: Learning a Good Initialization and Inducing Descriptor Post-enhancing for Large-scale Place Recognition

Large-scale place recognition is a fundamental but challenging task, whi...

Please sign up or login with your details

Forgot password? Click here to reset