TY - GEN
T1 - A Unique Method for Detecting Grounds in the Indoor Environment
AU - Chen, Xiaoxiao
AU - Song, Ping
AU - Zhai, Yayu
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In this paper, a unique method for detecting and distinguishing the grounds, walls, and ceilings in the indoor environment using single depth image is presented. Our method combines clustering and recognition to estimate the planes show in the depth image. A depth image correction method is proposed. Clustering process using k-means algorithm. The number of clusters is determined by elbow method. Recognition process using HOD (histogram of distance)to classify the planes. The classification of grounds walls and ceilings is very useful in mobile robot navigation, people detection and many other situations. Different from other existing methods, our method is fully automated, and only need one single depth image, no need to know the position and posture of the camera. On the basis of a certain number of experiments, we demonstrate the usefulness and robustness of our method. Our method is ready to be used in many other situations like path planning, target following, map reconstructing, etc.
AB - In this paper, a unique method for detecting and distinguishing the grounds, walls, and ceilings in the indoor environment using single depth image is presented. Our method combines clustering and recognition to estimate the planes show in the depth image. A depth image correction method is proposed. Clustering process using k-means algorithm. The number of clusters is determined by elbow method. Recognition process using HOD (histogram of distance)to classify the planes. The classification of grounds walls and ceilings is very useful in mobile robot navigation, people detection and many other situations. Different from other existing methods, our method is fully automated, and only need one single depth image, no need to know the position and posture of the camera. On the basis of a certain number of experiments, we demonstrate the usefulness and robustness of our method. Our method is ready to be used in many other situations like path planning, target following, map reconstructing, etc.
KW - Ground plane estimation
KW - Machine learning
KW - Three-dimensional radar
UR - http://www.scopus.com/inward/record.url?scp=85063648634&partnerID=8YFLogxK
U2 - 10.1109/ICSESS.2018.8663712
DO - 10.1109/ICSESS.2018.8663712
M3 - Conference contribution
AN - SCOPUS:85063648634
T3 - Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
SP - 540
EP - 544
BT - ICSESS 2018 - Proceedings of 2018 IEEE 9th International Conference on Software Engineering and Service Science
A2 - Wenzheng, Li
A2 - Babu, M. Surendra Prasad
PB - IEEE Computer Society
T2 - 9th IEEE International Conference on Software Engineering and Service Science, ICSESS 2018
Y2 - 23 November 2018 through 25 November 2018
ER -
