Class-specific Anchoring Proposal for 3D Object Recognition in LIDAR and RGB Images

07/22/2019
by   Amir Hossein Raffiee, et al.
10

Detecting objects in a two-dimensional setting is often insufficient in the context of real-life applications where the surrounding environment needs to be accurately recognized and oriented in three-dimension (3D), such as in the case of autonomous driving vehicles. Therefore, accurately and efficiently detecting objects in the three-dimensional setting is becoming increasingly relevant to a wide range of industrial applications, and thus is progressively attracting the attention of researchers. Building systems to detect objects in 3D is a challenging task though, because it relies on the multi-modal fusion of data derived from different sources. In this paper, we study the effects of anchoring using the current state-of-the-art 3D object detector and propose Class-specific Anchoring Proposal (CAP) strategy based on object sizes and aspect ratios based clustering of anchors. The proposed anchoring strategy significantly increased detection accuracy's by 7.19 Moderate and Hard setting of the pedestrian class, 2.19 Easy, Moderate and Hard setting of the car class and 12.1 cyclist class. We also show that the clustering in anchoring process also enhances the performance of the regional proposal network in proposing regions of interests significantly. Finally, we propose the best cluster numbers for each class of objects in KITTI dataset that improves the performance of detection model significantly.

READ FULL TEXT

page 3

page 6

page 7

research
03/02/2022

Dense Voxel Fusion for 3D Object Detection

Camera and LiDAR sensor modalities provide complementary appearance and ...
research
11/01/2021

VPFNet: Voxel-Pixel Fusion Network for Multi-class 3D Object Detection

Many LiDAR-based methods for detecting large objects, single-class objec...
research
09/06/2022

CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusion

3D Multi-object tracking (MOT) ensures consistency during continuous dyn...
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
03/16/2018

Complex-YOLO: Real-time 3D Object Detection on Point Clouds

Lidar based 3D object detection is inevitable for autonomous driving, be...
research
04/08/2021

Enhancing Object Detection for Autonomous Driving by Optimizing Anchor Generation and Addressing Class Imbalance

Object detection has been one of the most active topics in computer visi...
research
08/03/2021

Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study

Advances in sensing and learning algorithms have led to increasingly mat...

Please sign up or login with your details

Forgot password? Click here to reset