The 3D object recognition with environmental adaptability based on VFH descriptor and region growing segmentation

Zhuang Peng,Meng Chen,Jinbao Chen,Dong Han

doi:10.21595/jme.2016.16050

Abstract

3D object recognition is a basic research in the machine vision field. Microsoft KINECT V2 is utilized to collect external environmental information. The point cloud file is obtained after processing the collected information. In order to filter the point cloud and obtain point cloud model of a single object in the environment after region growing segmentation, the point cloud is applied to point cloud library. Then, the VFH descriptor of the point cloud model is calculated. After inputting point cloud model of the trained target, the point cloud model with the minimum CHI square distance between the VFH descriptor of the target and VFH descriptor of the point cloud model can be found. The 3D object corresponding to the found model is the identified object. For the 3D object recognition in an unfamiliar environment, the algorithm of 3D object recognition with environmental adaptability is proposed. After the 3D object recognition system built, the physical verification is conducted about the proposed algorithm. Giving the target model, the system successfully identifies the 3D object in the unfamiliar environment, that demonstrates the correctness of the algorithm.

Highlights

In order to identify the object in the unfamiliar environment, this paper proposes a method which adjusts the parameter dynamically so that the region growing segmentation can adapt to the environment
VFH descriptor is used to describe the object feature, and the target object is judged by CHI square distance of VFH descriptors
VFH descriptor consists of an extended FPFH of center point and the angle between the central viewpoint direction translated to each normal

Summary

Introduction

In order to identify the object in the unfamiliar environment, this paper proposes a method which adjusts the parameter dynamically so that the region growing segmentation can adapt to the environment. VFH descriptor is used to describe the object feature, and the target object is judged by CHI square distance of VFH descriptors. The research builds the 3D object recognition. THE 3D OBJECT RECOGNITION WITH ENVIRONMENTAL ADAPTABILITY BASED ON VFH DESCRIPTOR AND REGION GROWING SEGMENTATION. It successfully identifies the irregular objects, that verifies the correctness of the method

Point cloud acquisition

Region growing segmentation

Compute VFH descriptor

Experimental verification

Findings

Conclusions