SemanticVoxels: Sequential Fusion for 3D Pedestrian Detection using LiDAR Point Cloud and Semantic Segmentation

09/25/2020
by   Juncong Fei, et al.
5

3D pedestrian detection is a challenging task in automated driving because pedestrians are relatively small, frequently occluded and easily confused with narrow vertical objects. LiDAR and camera are two commonly used sensor modalities for this task, which should provide complementary information. Unexpectedly, LiDAR-only detection methods tend to outperform multisensor fusion methods in public benchmarks. Recently, PointPainting has been presented to eliminate this performance drop by effectively fusing the output of a semantic segmentation network instead of the raw image information. In this paper, we propose a generalization of PointPainting to be able to apply fusion at different levels. After the semantic augmentation of the point cloud, we encode raw point data in pillars to get geometric features and semantic point data in voxels to get semantic features and fuse them in an effective way. Experimental results on the KITTI test set show that SemanticVoxels achieves state-of-the-art performance in both 3D and bird's eye view pedestrian detection benchmarks. In particular, our approach demonstrates its strength in detecting challenging pedestrian cases and outperforms current state-of-the-art approaches.

READ FULL TEXT

page 1

page 6

research
11/22/2019

PointPainting: Sequential Fusion for 3D Object Detection

Camera and lidar are important sensor modalities for robotics in general...
research
09/07/2022

MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection

Fusing LiDAR and camera information is essential for achieving accurate ...
research
07/14/2023

LEST: Large-scale LiDAR Semantic Segmentation with Transformer

Large-scale LiDAR-based point cloud semantic segmentation is a critical ...
research
10/17/2017

Combining LiDAR Space Clustering and Convolutional Neural Networks for Pedestrian Detection

Pedestrian detection is an important component for safety of autonomous ...
research
07/15/2019

Improving 3D Object Detection for Pedestrians with Virtual Multi-View Synthesis Orientation Estimation

Accurately estimating the orientation of pedestrians is an important and...
research
06/17/2020

LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB

While short range 3D pedestrian detection is sufficient for emergency br...
research
03/02/2022

Improving Lidar-Based Semantic Segmentation of Top-View Grid Maps by Learning Features in Complementary Representations

In this paper we introduce a novel way to predict semantic information f...

Please sign up or login with your details

Forgot password? Click here to reset