Object pose and surface material recognition using a single-time-of-flight camera  

作　　者：Dongzhao Yang Dong An Tianxu Xu Yiwen Zhang Qiang Wang Zhongqi Pan Yang Yue 

机构地区：[1]Xi’an Jiaotong University,School of Information and Communications Engineering,Xi’an,China [2]Nankai University,Institute of Modern Optics,Tianjin,China [3]Zhengzhou University,School of Electrical and Information Engineering,National Center for International Joint Research of Electronic Materials and Systems,Zhengzhou,China [4]Angle AI(Tianjin)Technology Co.Ltd.,Tianjin,China [5]University of Louisiana at Lafayette,Department of Electrical and Computer Engineering,Lafayette,Louisiana,United States

出　　处：《Advanced Photonics Nexus》2024年第5期21-37,共17页先进光子学通讯（英文）

基　　金：supported by the Shaanxi Province Innovation Talent Promotion Program-Science and Technology Innovation Team(Grant No.2023-CX-TD-03).

摘　　要：We propose an approach for recognizing the pose and surface material of diverse objects,leveraging diffuse reflection principles and data fusion.Through theoretical analysis and the derivation of factors influencing diffuse reflection on objects,the method concentrates on and exploits surface information.To validate the feasibility of our theoretical research,the depth and active infrared intensity data obtained from a single time-of-flight camera are initially combined.Subsequently,these data undergo processing using feature extraction and lightweight machine-learning techniques.In addition,an optimization method is introduced to enhance the fitting of intensity.The experimental results not only visually showcase the effectiveness of our proposed method in accurately detecting the positions and surface materials of targets with varying sizes and spatial locations but also reveal that the vast majority of the sample data can achieve a recognition accuracy of 94.8%or higher.

关 键 词：data fusion TIME-OF-FLIGHT object detection diffuse reflection principles machine learning 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]